European Neuropsychopharmacology 60 (2022) 55–75 
www.elsevier.com/locate/euroneuro 
The U-shaped relationship between 
parental age and the risk of bipolar 
disorder in the offspring: A systematic 
review and meta-analysis 
Giovanna Fico a , Vincenzo Oliva a , b , Michele De Prisco a , c , 
Anna Giménez-Palomo a , Maria Sagué-Vilavella a , 
Susana Gomes-da-Costa a , Marina Garriga a , Eva Soléa , 
Marc Valentía , Giuseppe Fanelli b , d , Alessandro Serretti b , 
Michele Fornaro c , Andre F Carvalho e , Eduard Vieta a , ∗, 
Andrea Murru a 
a Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, IDIBAPS, CIBERSAM, 
University of Barcelona, 170 Villarroel st, 12-0, Barcelona, Catalonia 08036, Spain 
b Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy 
c Department of Neuroscience, Section of Psychiatry, Reproductive Science and Odontostomatology, 
Federico II University of Naples, Naples, Italy 
d Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud 
University Medical Center, Nijmegen, the Netherlands 
e IMPACT - the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, 
Geelong, Vic., Australia 6 Perinatal Health Unit, Hospital Clinic, IDIBAPS, CIBERSAM, University of 
Barcelona, Deakin University, Barcelona, Catalonia, Spain 
Received 27 March 2022; received in revised form 2 May 2022; accepted 10 May 2022 
KEYWORDS 
Bipolar disorder; 
Parental age; 
Maternal age; 
Abstract 
Parenthood age may affect the risk for the development of different psychiatric disorders in 
the offspring, including bipolar disorder (BD). The present systematic review and meta-analysis 
aimed to appraise the relationship between paternal age and risk for BD and to explore the 
eventual relationship between paternal age and age at onset of BD. We searched the MEDLINE, 
∗ Corresponding author. 
E-mail address: evieta@clinic.cat (E. Vieta). 
https://doi.org/10.1016/j.euroneuro.2022.05.004 
0924-977X/ © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license 
( http://creativecommons.org/licenses/by/4.0/ ) 
G. Fico, V. Oliva, M. De Prisco et al. 
Paternal age; 
Offspring; 
Meta-analysis 
Scopus, Embase, PsycINFO online databases for original studies from inception, up to December 
2021. Random-effects meta-analyses were conducted. 
Sixteen studies participated in the qualitative synthesis, of which k = 14 fetched quantita- 
tive data encompassing a total of 13,424,760 participants and 217,089 individuals with BD. 
Both fathers [adjusted for the age of other parent and socioeconomic status odd ratio –
OR = 1.29(95%C.I. = 1.13–1.48)] and mothers aged ≤ 20 years [(OR = 1.23(95%C.I. = 1.14–1.33)] 
had consistently increased odds of BD diagnosis in their offspring compared to parents aged 25–
29 years. Fathers aged ≥ 45 years [adjusted OR = 1.29 (95%C.I. = 1.15–1.46)] and mothers aged 
35–39 years [OR = 1.10(95%C.I. = 1.01–1.19)] and 40 years or older [OR = 1.2(95% C.I. = 1.02–
1.40)] likewise had inflated odds of BD diagnosis in their offspring compared to parents aged 
25–29 years. 
Early and delayed parenthood are associated with an increased risk of BD in the offspring. 
Mechanisms underlying this association are largely unknown and may involve a complex inter- 
play between psychosocial, genetic and biological factors, and with different impacts accord- 
ing to sex and age range. Evidence on the association between parental age and illness onset is 
still tentative but it points towards a possible specific effect of advanced paternal age on early 
BD-onset. 
© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY 
license ( http://creativecommons.org/licenses/by/4.0/ ) 
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P. Introduction 
 basic tenet of psychiatry is that the disease phenotype 
esults from a combination of genetic and environmental 
ffects. Indeed, bipolar disorder (BD) is a severe psychiatric 
ondition with a prevalence in the general population of 2% 
 Carvalho et al., 2020 ) and an estimated family- and twin- 
ased heritability of 60–85% ( McGuffin et al., 2003 ). How- 
ver, genetics only explains a part of the etiology of BD, 
hereby a growing body of evidence has related diverse el- 
ments of the environment that may influence the risk for 
D ( Bortolato et al., 2017 ). The broad range of environmen- 
al risk factors vary on time of exposure and may include 
oth pre- or peri-natal factors, adverse childhood experi- 
nces, infections, as well as urbanization, migration, ma- 
or stressful life events, and the misuse of drugs or alco- 
ol ( Blanco et al., 2017 ; Grant et al., 2005 ; Kessing et al.,
004 ; Pacchiarotti et al., 2013 ; Vieta, 2014 ). Globally, en- 
ironmental factors contribute up to 32% of the risk of BD 
 Polderman et al., 2015 ), proving to be appealing poten- 
ially modifiable targets for preventive strategies. 
Parental age is a well-known factor involving environ- 
ental and genetic contributions that impacts the risk 
f several disorders in the offspring ( Malaspina et al., 
015 ; Reichenberg et al., 2006 ). Both extremes of the 
eproductive age have been associated with worse out- 
omes, either regarding mother’s age, father’s age, or both 
 McGrath et al., 2014 ). A notable example is the higher 
isk of Down’s syndrome in older mothers ( Mai et al., 
013 ), while a younger childbearing age is associated with 
ducational underachievement, juvenile crimes, substance 
isuse, and mental health problems ( D’Onofrio et al., 
014a ; Sujan et al., 2022 ). Advanced paternal age at 
irth has been associated with an increased incidence 
f several neurodevelopmental and psychiatric disorders, 
ncluding schizophrenia and autism spectrum disorders 
 Khachadourian et al., 2021 ; Reichenberg et al., 2006 ). 
echanisms underlying these relationships are not fully un- 
erstood, with findings suggesting a role for de-novo mu- 
ations in the male germline ( Fromer et al., 2014 ; 56 alaspina, 2001 a) or even a greater likelihood for preg- 
ancy complications which are more common with delayed 
arenthood ( Chudal et al., 2017 ; Garcia-Rizo and Bitani- 
irwe, 2020 ; Giménez et al., 2019 ; Talati et al., 2013 ). Also,
dvanced paternal age seems to increase the risk for early- 
nset psychoses due to the possible role of accumulating 
ge-related DNA mutations ( Wang et al., 2019 ). 
However, there is still discordant evidence on the as- 
ociation between advanced parental age and risk of BD 
n the offspring, with some large studies proving the posi- 
ive association between advanced paternal age and BD risk 
 D’Onofrio et al., 2014 a; Frans et al., 2008 a; Weiser et al.,
020 ), whilst others have shown no significant association 
 Buizer-Voskamp et al., 2011 ; McGrath et al., 2014 ). 
Considering the increasing trend in average parental age 
Bray et al., 1978), the elucidation of such an association 
ight have societal and public health implications. Also, 
vidence of parental age effects on BD risk may provide in- 
ights into the etiology of this complex, multifactorial dis- 
rder. 
Thus, the first aim of this systematic review and meta- 
nalysis is to determine whether parental age is associated 
ith an increased risk of BD in the offspring. Also, consider- 
ng that early-onset BD displays homogeneous characteris- 
ics and that specific risk factors might operate in this sub- 
roup ( Chengappa et al., 2003 ; Connor et al., 2017 ), a sec-
ndary aim is to assess whether advanced parental age is 
ssociated with an earlier onset of BD. 
. Material and methods 
he present Systematic Review and Meta-analysis was conducted 
ccording to the 2020 version of the Preferred Reporting Items 
or Systematic Reviews and Meta-Analyses (PRISMA) guidelines 
 Page et al., 2021 ) and the Meta-analysis of Observational Stud-
es in Epidemiology (MOOSE) ( Stroup, et al., 2000 ) (Supplemen- 
ary 1 and 2). The protocol of this systematic review and meta-
nalysis was registered on the International Prospective Register 
f Systematic Reviews (PROSPERO) ( https://www.crd.york.ac.uk/ 
ROSPERO/ ; protocol CRD42021293319). 
European Neuropsychopharmacology 60 (2022) 55–75 
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2.1. Eligibility criteria and study outcomes 
riginal studies were eligible for inclusion if: (i) the study popula- 
ion consisted of people with BD diagnosed according to the Diag- 
ostic and Statistical Manual for Mental Disorders (DSM) any edition 
 APA, 1994 , 2013 ) or the International Classification of Diseases 
ICD) any edition (WHO 2004) diagnostic criteria with validated di- 
gnosis through structured interviews, and the same criteria had 
o be applied also to the non-BD group to exclude the presence of
sychiatric diagnoses; (ii) they examined maternal and/or paternal 
ge as the variable of interest; (iii) they assessed the association 
etween advanced parental age and risk of BD; (iv) they used a 
tandardized format for presentation of data, allowing for compar- 
sons between studies and calculation of crude ORs. No restrictions 
bout language were applied. Whenever multiple studies consid- 
red overlapping study populations, the largest one with the most 
omplete data was included. Reviews, case reports, case series, 
nd studies conducted on animals were excluded. 
.2. Search strategy 
he PubMed/MEDLINE, EMBASE, Scopus, and PsycINFO databases 
ere systematically searched from inception until December 1st, 
021. The following string was adopted for the PubMed/MEDLINE 
earch: ((bipolar disorder[MeSH Terms]) OR (bipolar disor- 
er[Title/Abstract])) OR (bipolar ∗[Title/Abstract])) AND ((parental 
ge[MeSH Terms]) OR (paternal age[Title/Abstract]) OR (maternal 
ge[Title/Abstract])) OR (age of mother[Title/Abstract]) OR (age 
f father[Title/Abstract]) OR (mother’s age[Title/Abstract]) OR (fa- 
her’s age[Title/Abstract]) OR (age of parents[Title/Abstract])). 
earch strings for the other databases are available in the Sup- 
lementary material. The references of each included study, text- 
ooks, and other material were hand searched to identify potential 
dditional studies not captured by the original search-string. 
.3. Study selection and data extraction 
wo independent reviewers (GF and MDP) independently screened 
ach study for eligibility. When a consensus could not be achieved, 
 third author (VO) was consulted. 
The following data were extracted (when applicable): author(s), 
ublication year, study design, geographical region, country, di- 
gnostic criteria considered, (semi)structured interview adopted, 
umber of BD cases, number of non-cases, BD type, age of BD onset,
irth years, estimates of relative risk of BD (odds ratios from case- 
ontrol or incidence rate ratios or hazard ratios from cohort stud- 
es), maternal and paternal age and how it was modeled (e.g., cat- 
gorically). In the case of studies fulfilling inclusion criteria without 
ully available raw data, authors were contacted up to 2 times to 
sk for data. For studies reporting data in figures only, WebPlotDigi- 
izer ( https://automeris.io/WebPlotDigitizer/ ) was used to extract 
ata from figures manually. 
.4. Methodological quality appraisal 
he risk of bias in the included studies was independently assessed 
y two authors (GF and MDP), and any disagreement was resolved 
y a third author (VO). The Newcastle-Ottawa Scale (NOS) ( Stang, 
010 ) was adopted to grade studies’ quality. 57 .5. Statistical analyses 
nalyses were performed using RStudio R version 4.1.2 ( RStudio 
eam, 2020 ) and the metafor R-package ( Viechtbauer 2010 ) using
 random-effect model (restricted maximum-likelihood estimator) 
 Harville, 1977 ). Effect sizes were calculated as odds ratios (ORs)
ith their confidence intervals (CIs) when parental age was consid- 
red as a categorical measure, and as standardized mean differ- 
nces (SMDs) with their CI when parental age was considered as a
ontinuous measure. Effect sizes adjusted for the age of the other 
arent and socioeconomic status - measured as paternal occupa- 
ion, ethnicity, education, or income ( Goldberg et al., 2011 ) - were
sed when available. 
Heterogeneity between studies was assessed by χ2 test of fit 
Cochrane Q test) and I 2 statistic. A χ2 statistic having p < 0.05 
nd I 2 statistic > 50% were considered suggestive of heterogeneity 
 Higgins et al., 2003 ). 
Sensitivity analyses were conducted by removing one study at 
ime from the analysis; cumulative analyses were performed to 
valuate the repercussions of the follow-up length and the year 
f enrollment on the effect size. Publication bias was explored by 
isual inspection of funnel plots and using the Egger’s test . If the
atter was significant, the trim-and-fill procedure was adopted to 
stimate the impact of the publication bias on the results. 
. Results 
.1. Study selection 
 flow diagram showing the results of the literature search 
nd selection of studies is presented in Fig. 1 . The literature
earch involving the electronic databases MEDLINE, Psych- 
nfo, Embase, and Scopus identified a total of 714 records. 
f these, 634 articles, including duplicates not fulfilling el- 
gibility criteria, were excluded. Thus, 80 full-text articles 
ere further evaluated for eligibility; of these, 64 were ex- 
luded for: (1) not including patients with BD, (2) not re- 
orting data on parental age, (3) not presenting original 
ata, (4) being congress abstracts. A final number of 16 ar- 
icles were included for their qualitative synthesis, and of 
hese, 14 were included in the quantitative syntheses. 
.2. Study characteristics 
emographic, clinical characteristics and main results of 
he studies included are presented in Table 1 . The in- 
luded 16 studies ( Birmaher et al., 2021 ; Brown et al., 
013 ; Buizer-Voskamp et al., 2011 ; Chudal et al., 
014 ; D’Onofrio et al., 2014 a; Fountoulakis et al., 
019 ; Frans et al., 2008 a; Grigoroiu-Serbanescu et al., 
012 ; Helenius et al., 2013 ; Laursen et al., 2007 ; 
ehrer et al., 2016 ; Liang et al., 2021 ; McGrath et al., 2014 ;
enezes et al., 2010 ; Seidman et al., 2013 ; Weiser et al.,
020 ) comprised a total 13,424,760 participants and 
17,089 individuals with BD. 
.2.1. Design 
f the 14 studies included in the meta-analyses, five re- 
orted only paternal age and the offspring’s risk of BD 
 Buizer-Voskamp et al., 2011 ; D’Onofrio et al., 2014 a; 
aursen et al., 2007 ; Menezes et al., 2010 ; Weiser et al.,
020 ), one only maternal age and the offspring’s risk of BD 
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Table 1 Demographic, clinical characteristics, and main results of the included studies. 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Laursen et al. 
(2007 ) 
Retrospective 
cohort study 
Denmark 1955- 
1987 
32 2,100,000 4349 Paternal: ≤20, 
21–25, 26–30, 
31–35, 36–40, 
41–45, 46-50, 
51-55, ≥56 
Adjusted for age, 
sex, family history 
of psychiatric 
admission, and 
maternal age. 
Paternal age reference: 21-25 
years (rate 0.11 cases/1000 
p-y). 
Significant higher relative risk 
at ranges: 
- 31-35 (RR 1.21, 95% CI 1.09, 
1.42). 
- 36-40 (RR 1.25, 95% CI 1.09, 
1.42). 
- 51-55 (RR 1.71 95% CI 1.21, 
2.41). 
Tendency to higher relative risk 
with age increase, with no 
statistical significance in 
ranges not reported. 
Included in 
quantitative 
analyses 
Frans et al. 
(2008 a) 
Case-Control Sweden 1932- 
1991 
39 13,428 
(mater- 
nal), 
13,428 
(paternal) 
107,140 
(mater- 
nal), 
67,140 
(paternal) 
Maternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, ≥ 45 
Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, 45-49, 
50-54, ≥ 55 
Adjusted for age 
of other parent 
and family history 
of psychotic 
disorder. 
Maternal age reference: 20-24 
years. 
Significant higher OR at ranges: 
- 30-34 (OR 1.07, 95% CI 1, 
1.15) 
- 35-39 (OR 1.15, 95% CI 1.05, 
1.25) 
Paternal age reference: 20-24 
years. 
- 30-34 (OR 1.13, 95% CI 1.03, 
1.20). 
- 35-39 (OR 1.11, 95% CI 1.01, 
1.21). 
- 40-44 (OR 1.17 95% CI 1.06, 
1.30). 
- 45-49 (OR 1.18, 95% CI 1.04, 
1.35) 
- 50-54 (OR 1.24, 95% CI 1.02, 
1.50). 
- ≥ 55 (OR 1.37, 95% CI 1.03, 
1.83). 
Included in 
quantitative 
analyses. 
Studying the 
relationship 
between 
parental age 
and age of BD 
onset. 
( continued on next page ) 
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Menezes et al. 
(2010 ) 
Retrospective 
cohort study 
Sweden 1973- 
1980 
28 711,496 493 Paternal: < 21, 
21-24, 25-29, 
30-34, 35-39, 
40-44, 45-49, ≥ 50 
Adjusted for 
subject’s sex and 
age, gestational 
age, family history 
of psychosis, 
parents’ highest 
socio-economic 
status in 1990, 
parents’ highest 
educational level 
in 1990 and 
maternal age. 
Paternal age reference: 21-24 
years. 
Significant higher OR at ranges: 
- 35-39 (OR 1.68, 95% CI 1.09, 
2.61) 
- 40-44 (OR 1.85, 95% CI 1.04, 
3.30) 
OR > 1 in all other ranges, with 
no statistical significance. 
Included in 
quantitative 
analyses 
Buizer- 
Voskamp et al. 
(2011) 
Case-Control Netherlands 1999- 
2008 
61 1121 1645 Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, ≥ 40 
Adjusted for 
average income of 
the neighborhood, 
difference in age 
between the 
father and the 
mother and the 
ethnic 
background. 
Paternal age reference: 25-29 
years. 
No statistical difference in any 
range, with highest OR (1.68, 
95% CI 0.94, 3.01) at < 20. 
Included in 
quantitative 
analyses 
Grigoroiu- 
Serbanescu et 
al. (2012 ) 
Retrospective 
cohort study 
Europe 14 564 
BDI 
Paternal: < 24, 
25-34, > 35 
Maternal: < 24, 
25-34, > 35 
Significant influence of 
increasing paternal age, and 
especially age > 35years, on age 
of onset of BD in the total 
sample (OR = 0.54, 
CI:0.35–0.80), in the female 
subsample (OR = 0.44, CI: 
0.25–0.78). 
Studying the 
relationship 
between 
parental age 
and age of BD 
onset 
Brown et al. 
(2013 ) 
Case-Control USA 1959- 
1966 
16 679 
(paternal), 
746 
(maternal) 
83 
(paternal), 
92 
(maternal) 
Paternal: 15-24, 
25-34, 35-44, ≥ 45 
Maternal: < 20, 
20-29, 30-39, ≥ 40 
Paternal: 
adjusted for 
maternal age. 
Maternal: adjusted 
for paternal age 
and maternal 
race. 
Paternal age reference: 25-34 
years. OR 1.45 at ≥ 45, 
non-statistically significant. No 
statistically significant 
differences with other ranges. 
Maternal age reference: 20-29 
years. OR 1.46 at ≥ 40, 
non-statistically significant. No 
statistically significant 
differences with other ranges. 
Included in the 
quantitative 
analyses 
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Seidman et al. 
(2013 ) 
Case-Control USA 1996- 
2007 
30 101 35 Mean age cases 
(maternal): 25.2 
years (SD 5.9). 
Mean age controls 
(maternal): 26.4 
years (SD 6). 
Cases with psychoses 
(schizophrenia or BD disorder) 
and controls were similar on 
age at testing, maternal age at 
birth of subject, socioeconomic 
status, and offspring sex. 
Included in 
quantitative 
analyses 
(means) 
Helenius et al. 
(2013 ) 
Case-Control Denmark 1950- 
1997 
59 3553 1204 Maternal: 15-35, 
35-52. Paternal: 
15-35, 35-64. 
Adjusted for 
family history of 
BD. 
Maternal age reference: 15-35 
years. 
Paternal age reference: 15-35 
years. 
Higher OR were observed in the 
second range of both maternal 
and paternal groups, which 
were not statistically 
significant. 
Significantly higher family load 
in the case-probands with pure 
BD than in the case-probands 
with BD comorbidities 
( p < 0.001). 
D’Onofrio et al. 
(2014 a) 
Retrospective 
cohort study 
Sweden 1973- 
1997 
28 2,615,081 6819 Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, ≥ 45 
Adjusted for 
maternal age at 
birth, 
socioeconomic 
status and year of 
birth. 
Paternal age reference: 20-24 
years. 
Significant higher OR at ranges: 
- 25-29 (OR 1.34, 95% CI 1.21, 
1.43) 
- 30-34 (OR 1.71, 95% CI 1.29, 
1.95) 
- 35-39 (OR 2.86, 95% CI 2.41, 
3.24) 
- 40-44 (OR 3.98, 95% CI 3.36, 
4.52) 
- ≥ 45 (OR 6.57, 95% CI 4.81, 
8.24) 
Significant lower OR at < 20 
group (OR 0.83, 95% CI 0.7, 
0.981). 
Included in 
quantitative 
analyses 
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
McGrath et al. 
(2014 ) 
Prospective 
cohort study 
Europe 1955- 
2011 
51 2,894,688 14,618 Maternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44 
Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, ≥ 45 
Adjusted for age 
of the other 
parent 
No significant association 
between parental age and BD 
Included in 
quantitative 
analyses 
Chudal et al. 
(2014 ) 
Case-Control Finland 1983- 
1998 
25 3643 (ma- 
ternal), 
3601 
(paternal) 
1861 (ma- 
ternal), 
1821 
(paternal) 
Maternal: < 20, 
20-24, 25-29, 
30-34, 35-39, ≥ 40 
Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, 45-49, ≥ 50 
Adjusted for other 
parent’s age, 
parental 
psychiatric history, 
parental 
educational level, 
and place of birth. 
Maternal age reference: 30-34 
years. No statistically 
significant differences with any 
ranges. 
Paternal age reference: 30-34 
years. 
Significant higher OR at ranges: 
- 20-24 (OR 1.35, 95% CI 1.06, 
1.72) 
- ≥ 50 (OR 2.84, 95% CI 1.32, 
6.12) 
Included in 
quantitative 
analyses 
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Lehrer et al. (2016) 
Case-Control USA 20 7658 1375 Paternal: 
- BD with 
psychosis: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, ≥ 45. 
- BD without 
psychosis: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, ≥ 45. 
BD with psychosis: 
Mean age (SD) 
cases/ controls 
[paternal: 31 (SD 
8.2)/ 30.3 (SD 
7.5)]; [maternal: 
28.1(SD 6.6)/ 27.5 
(SD 6.4)]. 
BD without 
psychosis: 
Mean age (SD) 
cases/ controls 
[paternal: 30.5 (SD 
7.4)/ 30.3 (SD 
7.5)]; [maternal: 
26 (SD 6.6)/ 27.5 
(SD 6.4)] 
Adjusted for 
difference 
between paternal 
and maternal 
ages, sex, race 
and age. 
Paternal age reference: 20-24 
years. 
Among BD with psychosis 
group, significant higher OR at 
≥ 45 subgroup (OR 1.939, 95% 
CI 1.411, 2.643). 
Among BD without psychosis 
group, significant lower OR at 
< 20 subgroup (OR 0.440, 95% 
CI 0.22, 0.798). 
No statistically significant 
differences observed in other 
age ranges. 
Included in 
quantitative 
analyses 
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Fountoulakis 
et al. (2019 ) 
Retrospective 
cohort study 
Greece 204 42 For BD depression: 
- Paternal: > 25, 
> 30, > 40. 
- Maternal: > 20, 
> 22, > 26, > 35. 
For BD mania: 
- Paternal: 25-30, 
30-40, > 40. 
- Maternal: 20-22, 
22-26, 26-35, > 35. 
Paternal age reference: none. 
For BD depression: 
- Paternal: higher OR observed 
at > 25 (OR 3.71, 95% CI 1.13, 
13.02), > 40 (6.06, 95% CI 1.84, 
19.89). 
No other statistically 
significant differences 
observed. 
For BD mania: 
- Paternal: higher OR observed 
at 25-30 (OR 12.38, 95% CI 
1.63, 94.09), 30-40 (OR 5.62, 
95% CI 1.97, 15.96), and > 40 
(OR 4.56, 95% CI 1.29, 16.11). 
- Maternal: higher OR observed 
at 22-26 (OR 12.64, 95% CI 
1.66, 96.05), and 26-35 (OR 
16.68, 95% CI 3.78, 73.66). 
Included in 
quantitative 
analyses 
(means) 
Weiser 
et al. (2020) 
Prospective 
cohort study 
Israel 1960- 
1991 
31 916,439 883 Paternal: 16-24, 
25-29, 30-34, 
35-39, 40-44, 
45-60 
Adjusted for 
maternal age at 
birth, 
socioeconomic 
status and year of 
birth. 
Paternal age reference: 25-29 
years. 
Significant higher OR at ranges: 
- 35-39 (OR 1.24, 95% CI 1.00, 
1.53) 
- 45-60 (OR 1.68, 95% CI 1.17, 
2.39) 
OR < 1 only at 16-24 (OR 0.91), 
with no statistically significant 
differences. 
Included in 
quantitative 
analyses 
( continued on next page ) 
63
 
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 Fico,
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 Prisco
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Table 1 ( continued ) 
Author(s), year Study Design Study 
Location 
Birth 
years 
Years of 
follow-up 
Controls/ 
Cohort 
BD Cases Classification of 
parental age 
Adjusted 
covariates 
Main results Comment 
Liang et al. 
(2021 ) 
Prospective 
cohort study 
Taiwan 1991- 
2004 
21 4,138,151 3287 (ma- 
ternal), 
3622 
(paternal) 
Maternal: < 20, 
20-24, 25-29, 
30-34, 35-39, ≥ 40 
Paternal: < 20, 
20-24, 25-29, 
30-34, 35-39, 
40-44, 45-49, ≥ 50 
Adjusted for 
demographic data 
(parental age at 
childbirth, sex of 
children, income, 
and residence). 
Maternal age reference: 25-29 
years. 
Significant higher OR at < 20 
group (OR 1.23, 95% CI 1.04, 
1.45). 
No statistically significant 
differences with other ranges. 
Paternal age reference: 25-29 
years. 
Significant higher OR at ≥ 50 
group (OR 1.87, 95% CI 1.33, 
2.64). 
Included in 
quantitative 
analyses 
Birmaher et al. 
(2021 ) 
Case-Control USA 9.6 99 17 Mean age 
cases/controls 
(maternal): 26.4 
years (SD 
5.2)/29.4 years 
(SD 5.5). 
Mean age 
cases/controls 
(paternal): 27.5 
(SD 7.1)/31.8 
years (SD 6.5). 
Adjusted for 
within family 
correlations, 
ethnicity, living 
with both 
biological parents, 
pharmacological 
treatment. 
Significant differences found 
between parental (both 
maternal and paternal) age and 
BD in offspring ( p < 0.05), with 
lower mean parental age in BD 
groups. 
Included in 
quantitative 
analyses 
(means) 
Abbreviations : BD: bipolar disorder; RR: relative risk; CI: confidence interval; OR: odds ratio; SD: standard deviation. 
64
 
European Neuropsychopharmacology 60 (2022) 55–75 
Fig. 1 PRISMA flowchart of systematic review search process. 
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g Seidman et al., 2013 ), and eight both paternal and mater- 
al age and the offspring’s risk of BD ( Birmaher et al., 2021 ;
rown et al., 2013 ; Chudal et al., 2014 ; Fountoulakis et al., 
019 ; Frans et al., 2008 a; Lehrer et al., 2016 ; Liang et al.,
021 ; McGrath et al., 2014 ). Parental age was reported as 
eans or ranges. 
.2.2. Outcomes 
ost of the studies included in the meta-analyses reported 
ffect size as adjusted OR. The minority of included stud- 65 es reported adjusted relative risk (RR), incidence rate ra- 
io (IRR), or hazard ratio (HR). As the proportion of out- 
ome was reported as rare (i.e., < 0.07%) in those stud- 
es, OR approximated well to other effect sizes, thus we 
ssumed these measures as equal to OR ( Schmidt and 
ohlmann, 2008 ; Zhang and Yu, 1998 ). 
Paternal age was categorized into the following age 
roups: < 20, 20–24, 25–29, 30–34, 35–39, 40–44, and  45 
ears. Maternal age was categorized into the following age 
roups: < 20, 20–24, 25–29, 30–34, 35–39,  40. The high- 
G. Fico, V. Oliva, M. De Prisco et al. 
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ne appraised by most of the included studies. For stud- 
es that had other over-age categories (i.e., 45–49, > 50), 
he highest category of parental age was chosen by con- 
idering the one appraised by most of the included studies 
 Chudal et al., 2014 ; Frans et al., 2008 a; Liang et al., 2021 ;
enezes et al., 2010 ). The calculated pooled OR between 
hese categories was included in the highest ones (  45 or 
 40 years). One study classified age into 10-year intervals 
 Brown et al., 2013 ), so it was included in the secondary 
eta-analysis of unadjusted data by calculating OR using 
he lowest age group as a reference (15–24). For this specific 
ase, we included only the calculated OR for the highest 
ge category of paternal age (  45 years) in the respective 
uantitative analysis. 
.3. Meta-analyses of studies 
s our main aim was to conduct a meta-analysis using data 
djusted for the confounding variables, and since the refer- 
nce category varied among studies, we conducted for each 
arental sex a first meta-analysis using the 25–29 age group 
s the reference category and only adjusted effect sizes, 
nd a second one using the 20–24 age group as reference 
ategory after calculating ORs from raw data if not already 
vailable as adjusted OR in the study. 
.3.1. Adjusted data with reference age 25–29 years 
aternal age. Meta-analysis was possible for 4 stud- 
es ( Buizer-Voskamp et al., 2011 ; Liang et al., 2021 ; 
cGrath et al., 2014 ; Weiser et al., 2020 ). All data were 
djusted for socioeconomic status and age of the mother at 
hildbirth. Compared to socioeconomic fathers aged 25–29 
ears, the random effects pooled estimates of the risk of 
D were as follows: 1.29 (95% CI: 1.13–1.48; I 2 = 0%) for 
ffspring of fathers younger than 20 years old; 0.98 (95% 
I: 0.86–1.10; I 2 = 63.9%) for offspring of fathers aged 20–
4 years old; 1.02 (95% CI: 0.95–1.09; I 2 = 42.2%) for off- 
pring of fathers aged 30-34 years old; 1.03 (95% CI: 0.91–
.16; I 2 = 69.3%) for offspring of fathers aged 35–39 years 
ld; 1.16 (95% CI: 0.97–1.38; I 2 = 62.3%) for offspring of 
athers aged 40–44 years old; and 1.29 (95% CI: 1.15–1.46; 
 
2 = 0%) for offspring of fathers older than 45 years old 
 Fig. 2 ) (Supplementary 4). 
aternal age. Meta-analysis was possible for 2 studies 
 Liang et al., 2021 ; McGrath et al., 2014 ). All data were
djusted for socioeconomic status and age of the father at 
hildbirth. Compared with mothers aged 25–29 years, the 
andom effects pooled estimates of the risk of BD were as 
ollows: 1.23 (95% CI: 1.14–1.33; I 2 = 0%) for offspring of 
others younger than 20 years old; 1.05 (95% CI: 1–1.10; 
 
2 = 0%) for offspring of mothers aged 20-24 years old; 1.04 
95% CI: 0.98–1.1; I 2 = 0%) for offspring of mothers aged 30–
4 years old; 1.10 (95% CI: 1.01–1.19; I 2 = 0%) for offspring 
f mothers aged 35-39 years old; and 1.2 (95% CI: 1.02–1.40; 
 
2 = 0%) for offspring of mothers older than 40 years old 
 Fig. 2 ) (Supplementary 5). 
.3.2. Unadjusted data with reference age 20–24 years 
aternal age. Meta-analysis was possible for 9 studies 
 Brown et al., 2013 ; Chudal et al., 2014 ; D’Onofrio et al.,66 014 a; Frans et al., 2008 a; Laursen et al., 2007 ; 
ehrer et al., 2016 ; Liang et al., 2021 ; Menezes et al., 2010 ;
eiser et al., 2020 ). Data are unadjusted for all the stud- 
es, except for D’Onofrio et al. (2014 b) (adjusted for ma- 
ernal age at birth and family history of psychiatric disor- 
ers) and Frans et al. (2008 b) (adjusted for maternal age at 
irth, socioeconomic status, and year of birth). Compared 
ith fathers aged 20–24 years, the random effects pooled 
stimates of the risk of BD were as follows: 1.02 (95% CI: 
.87–1.20; I 2 = 52.2%) for offspring of fathers younger than 
0 years old; 1.05 (95% CI: 0.94–1.19; I 2 = 86.5%) for off-
pring of fathers 25-29 years old; 1.12 (95% CI: 0.93–1.35; 
 
2 = 91.1%) for offspring of fathers 30-34 years old; 1.23 
95% CI: 0.94–1.60; I 2 = 95.8%) for offspring of fathers 35–
9 years old; 1.34 (95% CI: 0.98–1.84; I 2 = 95.3%) for off-
pring of fathers 40–44 years old; and 1.58 (95% CI: 1.04–
.39; I 2 = 92.9%) for offspring of fathers older than 45 years 
ld ( Fig. 3 ) (Supplementary 4). 
aternal age. Meta-analysis was possible for 3 studies 
 Chudal et al., 2014 ; Frans et al., 2008 a; Liang et al.,
021 ). Data were unadjusted for all the studies, except for 
rans et al. (2008 b) (adjusted for maternal age at birth, 
ocioeconomic status, and year of birth). Compared with 
others aged 20–24 years, the random effects pooled es- 
imates of the risk of BD were as follows: 1.20 (95% CI: 0.95–
.53; I 2 = 82.8%) for offspring of mothers younger than 20 
ears old; 0.96 (95% CI: 0.84–1.11; I 2 = 85.4%) for offspring 
f mothers aged 25-29 years old; 0.96 (95% CI: 0.8–1.15; 
 
2 = 88.4%) for offspring of mothers aged 30-34 years old; 
.07 (95% CI: 0.95–1.2; I 2 = 54.2%) for offspring of mothers 
ged 35–39 years old; 1.1 (95% CI: 0.99–1.23; I 2 = 0%) for 
ffspring of mothers older than 40 years old ( Fig. 3 ) (Sup-
lementary 5). 
.3.3. Means 
aternal age. Meta-analysis was possible for 4 studies 
 Birmaher et al., 2021 ; Buizer-Voskamp et al., 2011 ; 
ountoulakis et al., 2019 ; Lehrer et al., 2016 ). When age 
as considered as mean, no evidence for an association be- 
ween paternal age and risk of BD in offspring emerged (SMD 
 0.07, 95% CI: -0.47-0.61). 
aternal age. Meta-analysis was possible for 4 stud- 
es ( Birmaher et al., 2021 ; Fountoulakis et al., 2019 ; 
ehrer et al., 2016 ; Seidman et al., 2013 ). When age was
onsidered as mean, no evidence for an association be- 
ween maternal age and risk of BD in offspring emerged 
SMD = 0.07, 95% CI: -0.50-0.64). 
.3.4. Sensitivity analyses 
n sensitivity analyses of paternal age considered as a cate- 
orical variable (adjusted data, reference age 25–29) and 
isk of BD, the direction of the combined estimates did 
ot significantly vary with the removal of each study in 
urn, except in the age category ≤ 20 in which, by remov- 
ng McGrath et al. (2014 ), the overall effect become non- 
ignificant and in the age category 40–44, in which by remov- 
ng Weiser et al. (2020), the overall effect become signifi- 
ant (OR = 1.27, 95% CI: 1.12–1.44). (Supplementary 6). In 
ensitivity analyses of maternal age considered as a categor- 
cal variable (adjusted data, reference age 25–29) and risk 
f BD in the age category 35–39, by removing McGrath et al. 
European Neuropsychopharmacology 60 (2022) 55–75 
Fig. 2 Pooled odds ratios (OR) with 95% CI for risk of BD by adjusted maternal and paternal age, with age of reference 25–29 years. 
Fig. 3 Pooled odds ratios (OR) with 95% CI for risk of BD by unadjusted paternal age, with age of reference 20–24 years. 
67 
G. Fico, V. Oliva, M. De Prisco et al. 
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p2014 ), the overall effect become non-significant (Supple- 
entary 6). 
.3.5. Cumulative analyses 
umulative analyses of the effect of the duration of the ob- 
ervation on paternal or maternal ages (both age of refer- 
nce 20–24 and 25–29) and the risk of BD in the offspring 
howed no statistically significant changes in the effect sizes 
s the duration of the follow-up increased (data available on 
equest). Cumulative analyses based on the year of sample 
nrollment across different studies showed no statistically 
ignificant changes in the effect sizes in almost every age- 
ange considered, with exception to the highest paternal 
ategory ( ≥ 45), which effect size became non-significant 
OR = 1.16, 95% CI: 0.97–1.38) as the year of enrollment 
as more recent (data available on request). 
.3.6. Publication bias 
n the analyses of paternal age group 20–24 and the risk 
f BD (reference age 25–29), the Egger’s tests and funnel 
lots were suggestive of publication bias (Egger’s t = -2.76, 
 = 0.0057), with two possible missing studies estimated 
ith the trim and fill method. In the analyses of paternal 
ge group ≥45 and the risk of BD (reference age 20–24), the 
gger’s tests and funnel plots were suggestive of publication 
ias (Egger’s t = 2.68, p = 0.007), with three possible miss- 
ng studies estimated with the trim and fill method. In the 
nalyses of maternal age groups 25-29, 30-34 and the risk 
f BD (reference age 20–24), the Egger’s tests and funnel 
lots were suggestive of publication bias (Egger’s t = -2.85, 
 = 0.004, and t = -3.30, p = 0.0009), with one possible 
issing study in each test estimated with the trim and fill 
ethod. All other analyses on publication bias using Egger’s 
est and inspection of funnel plots were not suggestive of 
ublication bias (data available on request). 
.3.7. Parental age effect on the age of onset of BD in 
he offspring 
nly two studies included in the narrative synthesis re- 
orted the effect of parental age on the age of onset 
f BD ( Frans et al., 2008 a; Grigoroiu-Serbanescu et al., 
012 ). Advanced paternal age was associated with earlier 
ge of BD onset in the first study ( Frans et al., 2008 a)
OR = 2.63; 95% CI, 1.19–5.81) and in the second study 
 Grigoroiu-Serbanescu et al., 2012 ), showing a negative as- 
ociation between increasing parental ages and decreasing 
roband age of BD onset (OR = 0.54, 95% CI, 0.35–0.80). 
aternal age had no significant effect on BD age of onset in 
oth studies (see Table 1 ). 
.3.8. Quality of the included studies 
verall, among case-control studies, 5 had “good" qual- 
ty and 2 were of “poor” quality overall, based on the 
ewcastle-Ottawa Scale (Supplementary 6). Overall, among 
ohort studies, 7 had “good” quality and 2 were of “poor”
uality overall, based on the Newcastle-Ottawa Scale (Sup- 
lementary 7). 
t
68 . Discussion 
.1. Main findings 
he present study aimed at quantifying, through a meta- 
nalytical approach, whether parental age is associated 
ith an increased risk of BD in the offspring and whether 
dvanced paternal age is associated with an early-onset of 
D. 
The main results of the quantitative analysis were: (i) 
ounger maternal and paternal ( ≤ 20 years) or advanced 
ge ( ≥ 35 or ≥ 45 years, respectively) were associated with 
n increased risk of BD in offspring when the reference age 
roup was 25–29 years and data were adjusted for confound- 
ng variables; (ii) when the reference age group was 20–24 
ears and the data were not adjusted for confounding vari- 
bles, only advanced paternal age ( ≥ 45 years) was associ- 
ted with an increased risk of BD in offspring; (iii) no signif- 
cant increase in the risk of BD in the offspring was found 
hen parental age was taken as means. 
Our results are in line with the ones of another recent 
eta-analysis on the topic ( Polga et al., 2022 ), in which 
dvanced paternal and maternal age were associated with 
 higher risk of BD in the offspring. However, this pre- 
ious quantitative analysis included a total of 7 studies 
nd did not consider two large prospective cohort stud- 
es ( Liang et al., 2021 ; McGrath et al., 2014 ), which re-
ruited over 6 million people and were included in the 
resent meta-analysis. Furthermore, the authors adopted 
ge categories of 10 years, possibly leaving residual con- 
ounding within categories ( Reijneveld, 2003 ), and used un- 
djusted effect sizes. Since the age of mothers and the 
ge of fathers are highly correlated, studies looking only 
t paternal age may show stronger effects, although the 
isks are attributable to maternal age ( Reijneveld, 2003 ). 
ndeed, nonlinear models examining the joint influence 
f paternal or maternal age and controlling for possible 
onfounders showed a better fit than traditional models 
 Thompson, 2019 ). Our results must therefore be considered 
n this light, with the adjusted results for confounding vari- 
bles being more reliable than the unadjusted ones. 
.2. Potential mechanisms 
he U-shaped association between BD risk in offspring and 
arental age showed in our results is not surprising, since 
he previous meta-analysis on schizophrenia or other neu- 
opsychiatric disorders also reported U-shaped risk patterns 
 Miller et al., 2011 ; Oldereid et al., 2018 ; Wu et al., 2017 ). 
There are several plausible underlying mechanisms by 
hich advanced parental age might increase the risk of BD 
n the offspring, that might derive from a complex interplay 
etween genetic and psychosocial factors. Interestingly, a 
ecent study investigating the association between poly- 
enic risk score for BD in parents and offspring and the risk 
f lifetime diagnosis of BD in offspring found that the role 
f genetic risk of the offspring is at least partially indepen- 
ent from clinical parental diagnosis of BD, explaining a big 
roportion of variance (5%) ( Birmaher et al., 2022 ). 
Our study is the first one that draws particular attention 
o the link between both younger paternal and maternal age 
European Neuropsychopharmacology 60 (2022) 55–75 
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2nd BD since previous meta-analyses on the matter failed 
o report this association as significant ( Polga et al., 2022 ). 
ounger parenthood has been associated with lower edu- 
ational achievements, adverse social outcomes, violent or 
riminal behavior both in parents and offspring ( Mills et al., 
011 ). Indeed, adolescent parents may experience more 
sychosocial stress, stigmatization, anxiety and use fewer 
oping strategies ( Kaye, 2008 ). Stressful life events might 
lso contribute to the increase of the risk of any mood 
isorders ( Hillegers et al., 2004 ; Kessing et al., 2003 ). In- 
reased rates of substance abuse including alcohol, co- 
aine, marijuana, and methamphetamines, are more com- 
on in younger parents ( Carroll Chapman and Wu, 2013 ; 
aldegan-Bueno et al., 2021 ). Also, adolescents might be 
ore prone to engage in non-protected sex, eventually re- 
ulting in unplanned pregnancies and increased rates of 
bortion ( Davis and Beasley, 2009 ). Therefore, evidence 
ighlighted a positive relationship between induced abor- 
ion, spontaneous abortion, and an increased risk of psy- 
hiatric disorders ( Jacob et al., 2019 ). Younger parents 
ith a tendency toward impulsive behavior, mood fluctua- 
ions, risky behaviors ( Axelson et al., 2011 ; Birmaher et al., 
018 ) or specific affective temperaments ( Fico et al., 2019 ) 
ight also be individuals with a prodrome affective disor- 
er, thus, with a higher genetic load and higher chances 
o progress to full-threshold BD ( Birmaher et al., 2018 ). 
owever, the recognized role of environmental factors as 
ues for BD risk should not overshadow the possible biolog- 
cal mechanism involved. Indeed, a stressful environment 
romotes inflammation ( Herbert and Cohen, 1993 ); there- 
ore, inflammation might be a mediator in the relationship 
etween psychosocial stress and offspring neuropsychiatric 
utcomes ( Csatlosova et al., 2021 ; Hantsoo et al., 2019 ; 
halfallah et al., 2022 ). Furthermore, stress exposure may 
ccelerate telomere shortening as observed in several psy- 
hiatric disorders, including BD. Telomere length is herita- 
le and correlates with paternal age ( Njajou et al., 2007 ), 
ut its role in increasing BD risk is unknown ( Slagboom et al., 
994 ). Still, a stressful environment rather than vertical 
ransmission may have a stronger influence on telomere 
hortening in BD ( Powell et al., 2018 ; Shalev et al., 2013 ;
aldes et al., 2005 ). Indeed, sperm telomere length in- 
reases with age in humans, and as a result offspring 
f older fathers inherit longer telomeres ( Eisenberg and 
uzawa, 2018 ). 
Substance use is associated with depression in the off- 
pring in pre-clinical studies ( Pacheco et al., 2021 ), and 
ith birth defects and increasing de novo mutations in 
ermlines in clinical studies ( Laubenthal et al., 2012 ; 
inschooten et al., 2013 ; Shi et al., 2001 ), which may ul- 
imately result in an increased risk for BD in the offspring of 
ounger parents. Nonetheless, most de novo mutations oc- 
ur in paternal germlines, while aneuploidies are mainly of 
aternal origin and are associated with increased maternal 
ge ( Larroya et al., 2021 ), but doubtfully associated with an 
ncreased paternal age ( Steiner et al., 2014 ). 
As regards advanced paternal age and the risk of BD, our 
esults replicated previous evidence ( Polga et al., 2022 ). 
he mechanism underlying the advanced parental age ef- 
ect has been mainly related to increased rates of de novo 
utations ( Crow, 2000 ; Kong et al., 2012 ), epigenetic al- 
ernations ( Denomme et al., 2020 ; Malaspina, 2001 a), and 69 he personality of older fathers ( Zammit et al., 2003 ). More 
ikely, a multitude of interacting factors seems to mediate 
he impact of advanced paternal age on BD risk, including 
he role of aging, de novo mutations, epigenetic mecha- 
isms, psychosocial environment, and selection into late fa- 
herhood ( Vervoort et al., 2022 ). 
For the mechanisms that underlie advanced maternal age 
ffects, evidence differs between BD and other neuropsy- 
hiatric disorders. It is well known that advanced maternal 
ge ( Cavazos-Rehg et al., 2015 )or a mother’s history of a se-
ere psychiatric disorder ( Solé et al., 2020 ) are associated 
ith higher rates of obstetric complications that might in- 
rease the risk of neurodevelopmental or psychiatric disor- 
ers in the offspring ( Zhang et al., 2019 ). However, while for
isorders such as schizophrenia and autism spectrum disor- 
er perinatal the association is replicated in several studies 
 Abel et al., 2013 ; Buchmayer et al., 2009 ; Davies et al.,
020 ), no significant association was found for BD, although 
vidence is still scarce ( Serati et al., 2020 ). Maternal im- 
une activation at the time of gestation, not limited to in- 
ections but considering a spectrum which includes stress 
r traumatic experiences, epigenetic modification of stress- 
elated pathways or changes in the microbiota, has been 
inked to increased risk of schizophrenia or BD ( Brown and 
onway, 2019 ). 
A secondary aim of our study was to assess whether 
arental age is associated with earlier BD onset, based on 
he hypothesis that advanced parental age increased the 
isk of early-onset BD in offspring. BD showed a bimodal 
early or late) or trimodal (early, mid- and late) age-of- 
nset distribution, probably due to a combined effect of 
nvironmental and genetic factors ( Bolton et al., 2021 ; 
essing, 2006 ; Preisig et al., 2016 ; Vedel Kessing et al., 
021 ), but to date, the paternal age effect on BD onset is
till to be explored. We found only two studies exploring this 
ssociation, not includable in quantitative analysis. Overall, 
oth studies indicated that advanced paternal, but no ma- 
ernal, age is associated with earlier age of BD onset. This 
esult is in line with the hypothesis that advanced age is as- 
ociated with an accumulation of DNA mutations, especially 
n paternal germ cells ( Taylor et al., 2019 ). 
.3. Clinical and preventative implications 
he combination of estimates from all previously published 
tudies allowed a more complete and precise assessment of 
he parental as a risk factor for BD, supporting the hypoth- 
sis that both very young and old parental age is associated 
ith an increased offspring’s risk for BD. In older parents, 
he effect on BD risk might have a stronger genetic or epi- 
enetic influence, while in younger fathers or mothers the 
ffect might result from a complex interaction between psy- 
hosocial environment, activation of stress-immune related 
athways, and epigenetic and genetic factors. 
For both clinical practice and public health programs, 
ur results underline the importance of applying prevention 
trategies to the patient population diagnosed with BD to 
inimize the risk of BD in the offspring, and to offspring 
hat would be identified as a BD risk population, along with 
ther known environmental risk factors ( Marangoni et al., 
016 ). However, due to the limitations of our study, such 
G. Fico, V. Oliva, M. De Prisco et al. 
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ronsiderations should be taken into account cautiously be- 
ore being translated into clinical practice. ( Laurenzi et al., 
020 )The progressively increased age of parenthood world- 
ide ( Waldenström, 2016 ; Eurostat, 2020) is a public health 
oncern, and future studies that demonstrate paternal age 
orrelates with specific psychiatric disorders may guide indi- 
idual and societal interventions. Lastly, although our data 
ere controlled for the presence of parental history of 
sychiatric disorders, it should be noted that offspring of 
arents with BD have an increased risk of developing any 
ood disorder ( Mesman et al., 2013 ), and specific preven- 
ive strategies in this at-risk population should be also im- 
roved. 
.4. Strengths and limitations 
ur study comes with some limitations. To begin, still few 
tudies investigated the association between parental age 
nd BD risk in offspring. Then, only observational stud- 
es were included in the analysis. Although there was 
oderate-to-high heterogeneity in some of the analyses, it 
as mostly limited to analysis with unadjusted data. Addi- 
ional information about non-psychotropic drugs, the course 
f pregnancy, the history of BD in first-degree relatives, the 
istory of other mood disorders in the parents, especially 
ith younger age and possible not-yet diagnosed with BD 
r other mood disorders, deserves additional primary stud- 
es to allow for control of such moderators. Although most 
tudies presented adjusted data for socioeconomic status, 
hey considered it as a single socioeconomic variable rather 
han a complex and multifactorial one ( Braveman et al., 
005 ). Also, although the majority of the pooled effect sizes 
n our quantitative analyses have a narrow confidence in- 
erval demonstrating a greater degree of precision, these 
ffect sizes are quite small, calling for caution. Finally, in 
he included studies the authors used a range of parental 
ge as a reference group, being able to assess the risk of BD 
n the offspring only in lower or higher parental age cate- 
ories compared to the reference points. However, several 
trengths should be addressed: we included a larger num- 
er of the studies on the topic confirming but, most impor- 
antly, significantly extending previous evidence; the major- 
ty of the included studies followed a longitudinal design, 
ith long follow-up periods; the pooled effect sizes of risk 
or BD were largely consistent in several different sensitiv- 
ty analyses; there was no publication bias in the majority 
f the analyses, so the probability that our findings are a 
esult of selective publication seems to be minimal. 
. Conclusion 
n conclusion, there is evidence that young and advanced 
arental age is associated with an increased risk of BD in 
he offspring. Recognition of this risk is of great importance 
n both clinical psychiatric practice and as a public health 
ssue. It is necessary to inform individuals on the risk of 
arly or delayed reproductive age and to implement inter- 
entions to reduce psychosocial stressors in adolescent par- 
nts, as well as programs to follow-up offspring at risk of 
eveloping BD. Further studies are needed to elucidate the 70 ause-effect relationship and mechanism between parental 
ge and increased risk of BD in the offspring. 
ole of the funding source 
he author(s) received no specific funding for this work. 
ontributors 
F designed the study and wrote the protocol, managed the 
iterature searches and analyses and wrote the first draft 
f the manuscript. Authors GF, MDP and VO undertook the 
tatistical analysis. All authors contributed to and have ap- 
roved the final manuscript. 
eclaration of Competing Interest 
V has received grants and served as consultant, advi- 
or, or CME speaker unrelated to the present work for 
he following entities: AB-Biotics, Abbott, Allergan, An- 
elini, Dainippon Sumitomo Pharma, Ferrer, Gedeon Richter, 
anssen, Lundbeck, Otsuka, Sage, Sanofi-Aventis, Sunovion, 
nd Takeda. GF has received CME-related honoraria, or con- 
ulting fees from Angelini, Janssen-Cilag and Lundbeck. MSV 
as received financial support for CME activities or travel 
unds from Janssen-Cilag and Lundbeck, and has served 
s a speaker for Casen Recordati. She reports no finan- 
ial or other relationship relevant to the subject of this 
rticle. AM has received funding unrelated to the present 
ork for research projects and/or honoraria as a consultant 
r speaker from the following entities: Angelini, Janssen, 
undbeck, Otsuka, Sanofi-Aventis and Spanish Ministry of 
cience and Innovation- Instituto de Salud Carlos III. SGC 
as received CME-related honoraria, or consulting fees from 
anssen-Cilag, Italfarmaco, Angelini and Lundbeck and re- 
orts no financial or other relationship relevant to the sub- 
ect of this article. AS is or has been a consultant/speaker 
or Abbott, Abbvie, Angelini, AstraZeneca, Clinical Data, 
oehringer, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, 
nnovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, 
fizer, Polifarma, Sanofi, and Servier. 
cknowledgments 
V thanks the support of the Spanish Ministry of Science 
nd Innovation (PI15/00283, PI18/00805) integrated into 
he Plan Nacional de I + D + I and co-financed by the ISCIII-
ubdirección General de Evaluación and the Fondo Europeo 
e Desarrollo Regional (FEDER); the Instituto de Salud Car- 
os III; the CIBER of Mental Health (CIBERSAM); the Secre- 
aria d’Universitats i Recerca del Departament d’Economia 
 Coneixement (2017 SGR 1365), the CERCA Programme, and 
he Departament de Salut de la Generalitat de Catalunya 
or the PERIS Grant SLT006/17/00357. AM has received a 
rant (PI19/00672) from the Instituto de Salud Carlos III 
ubdirección General de Evaluación y Fomento de la inves- 
igación, Plan Nacional 2019-2022. The project that gave 
ise to these results received the support of a fellowship 
European Neuropsychopharmacology 60 (2022) 55–75 
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Drom "La Caixa" Foundation (ID 100010434). GF fellowship 
ode is LCF/BQ/DR21/11880019. Thanks the support of the 
uropean Union Horizon 2020 research and innovation pro- 
ram (EU.3.1.1. Understanding health, wellbeing and dis- 
ase: Grant No 754907 and EU.3.1.3. Treating and managing 
isease: Grant No 945151). 
upplementary materials 
upplementary material associated with this article can be 
ound, in the online version, at doi: 10.1016/j.euroneuro. 
022.05.004 . 
eferences 
bel, K.M., Dalman, C., Svensson, A.C., Susser, E., Dal, H., 
Idring, S., Webb, R.T., Rai, D., Magnusson, C., 2013. Deviance 
in fetal growth and risk of autism spectrum disorder. Am. J. Psy- 
chiatry 170, 391–398. doi: 10.1176/APPI.AJP.2012.12040543 . 
PA, 1994. Diagnostic and Statistical Manual of Mental Disorders: 
DSM-5, 4th ed. APA, Washington DC . 
PA, 2013. Diagnostic and Statistical Manual of Mental Disorders : 
DSM-5. American Psychiatric Association, Arlington, VA. 
xelson, D.A., Birmaher, B., Strober, M.A., Goldstein, B.I., Ha, W., 
Gill, M.K., Goldstein, T.R., Yen, S., Hower, H., Hunt, J.I., 
Liao, F., Iyengar, S., Dickstein, D., Kim, E., Ryan, N.D., 
Frankel, E., Keller, M.B., 2011. Course of subthreshold bipolar 
disorder in youth: diagnostic progression from bipolar disorder 
not otherwise specified. J. Am. Acad. Child Adolesc. Psychiatry 
50. doi: 10.1016/J.JAAC.2011.07.005 . 
irmaher, B., Hafeman, D., Merranko, J., Zwicker, A., Gold- 
stein, B., Goldstein, T., Axelson, D., Monk, K., Hickey, M.B., 
Sakolsky, D., Iyengar, S., Diler, R., Nimgaonkar, V., Uher, R., 
2022. Role of polygenic risk score in the familial transmission 
of bipolar disorder in youth. JAMA Psychiatry 79. doi: 10.1001/ 
JAMAPSYCHIATRY.2021.3700 . 
irmaher, B., Merranko, J., Hafeman, D., Goldstein, B.I., Diler, R., 
Levenson, J.C., Monk, K., Iyengar, S., Hickey, M.B., Sakolsky, D., 
Axelson, D., Goldstein, T., 2021. A longitudinal study of psychi- 
atric disorders in offspring of parents with bipolar disorder from 
preschool to adolescence. J. Am. Acad. Child Adolesc. Psychia- 
try 60, 1419–1429. doi: 10.1016/J.JAAC.2021.02.023 . 
irmaher, B., Merranko, J.A., Goldstein, T.R., Gill, M.K., Gold- 
stein, B.I., Hower, H., Yen, S., Hafeman, D., Strober, M., 
Diler, R.S., Axelson, D., Ryan, N.D., Keller, M.B., 2018. A risk 
calculator to predict the individual risk of conversion from sub- 
threshold bipolar symptoms to bipolar disorder I or II in youth. J. 
Am. Acad. Child Adolesc. Psychiatry 57, 755–763. doi: 10.1016/ 
J.JAAC.2018.05.023 , e4 . 
lanco, C., Compton, W.M., Saha, T.D., Goldstein, B.I., Ruan, W.J., 
Huang, B., Grant, B.F., 2017. Epidemiology of DSM-5 bipolar I 
disorder: results from the national epidemiologic survey on al- 
cohol and related conditions – III. J. Psychiatr. Res. 84, 310–317. 
doi: 10.1016/j.jpsychires.2016.10.003 . 
olton, S., Warner, J., Harriss, E., Geddes, J., Saunders, K.E.A., 
2021. Bipolar disorder: trimodal age-at-onset distribution. Bipo- 
lar Disord. 23, 341. doi: 10.1111/BDI.13016 . 
ortolato, B., Köhler, C.A., Evangelou, E., León-Caballero, J., 
Solmi, M., Stubbs, B., Belbasis, L., Pacchiarotti, I., Kessing, L.V., 
Berk, M., Vieta, E., Carvalho, A.F., 2017. Systematic assessment 
of environmental risk factors for bipolar disorder: an umbrella 
review of systematic reviews and meta-analyses. Bipolar Disord. 
19, 84–96. doi: 10.1111/BDI.12490 . 
raveman, P.A., Cubbin, C., Egerter, S., Chideya, S., Marchi, K.S., 
Metzler, M., Posner, S., 2005. Socioeconomic status in health re- 71 search: one size does not fit all. JAMA 294, 2879–2888. doi: 10. 
1001/JAMA.294.22.2879 . 
rown, A., Bao, Y., McKeague, I., Shen, L., Schaefer, C., 2013. 
Parental age and risk of bipolar disorder in offspring. Psychia- 
try Res. 208, 225–231. doi: 10.1016/j.psychres.2013.05.024 . 
rown, A.S., Conway, F., 2019. Maternal immune activation and re- 
lated factors in the risk of offspring psychiatric disorders. Front. 
Psychiatry 10, 430. doi: 10.3389/FPSYT.2019.00430/BIBTEX . 
uchmayer, S., Johansson, S., Johansson, A., Hultman, C.M., 
Sparén, P., Cnattingius, S., 2009. Can association between 
preterm birth and autism be explained by maternal or neona- 
tal morbidity? Pediatrics 124, e817–e825. doi: 10.1542/PEDS. 
2008-3582 . 
uizer-Voskamp, J.E., Laan, W., Staal, W.G., Hennekam, E.A.M., 
Aukes, M.F., Termorshuizen, F., Kahn, R.S., Boks, M.P.M., 
Ophoff, R.A., 2011. Paternal age and psychiatric disorders: find- 
ings from a Dutch population registry. Schizophr. Res. 129, 128–
132. doi: 10.1016/J.SCHRES.2011.03.021 . 
arroll Chapman, S.L., Wu, L.T., 2013. Substance use among ado- 
lescent mothers: a review. Child. Youth Serv. Rev. 35, 806. 
doi: 10.1016/J.CHILDYOUTH.2013.02.004 . 
arvalho, A.F., Firth, J., Vieta, E., 2020. Bipolar disorder. N. Engl. 
J. Med. 383, 58–66. doi: 10.1056/NEJMra1906193 . 
avazos-Rehg, P.A., Krauss, M.J., Spitznagel, E.L., Bommarito, K., 
Madden, T., Olsen, M.A., Subramaniam, H., Peipert, J.F., 
Bierut, L.J., 2015. Maternal age and risk of labor and delivery 
complications. Matern. Child Health J. 19, 1202. doi: 10.1007/ 
S10995- 014- 1624- 7 . 
hengappa, K.N.R., Kupfer, D.J., Frank, E., Houck, P.R., Grochocin- 
ski, V.J., Cluss, P.A., Stapf, D.A., 2003. Relationship of birth co- 
hort and early age at onset of illness in a bipolar disorder case
registry. Am. J. Psychiatry 160, 1636–1642. doi: 10.1176/appi. 
ajp.160.9.1636 . 
hudal, R., Gissler, M., Sucksdorff, D., Lehti, V., Suominen, A., 
Hinkka-Yli-Salomäki, S., Brown, A.S., Sourander, A., 2014. 
Parental age and the risk of bipolar disorders. Bipolar Disord. 
16, 624–632. doi: 10.1111/BDI.12182 . 
hudal, R., Sourander, A., Surcel, H.M., Sucksdorff, D., Hinkka- 
Yli-Salomäki, S., Brown, A.S., 2017. Gestational maternal C- 
reactive protein and risk of bipolar disorder among young in- 
dividuals in a nationwide birth cohort. J. Affect. Disord. 208, 
41–46. doi: 10.1016/J.JAD.2016.08.056 . 
onnor, D.F., Ford, J.D., Pearson, G.S., Scranton, V.L., Dusad, A., 
2017. Early-onset bipolar disorder: characteristics and outcomes 
in the clinic. J. Child Adolesc. Psychopharmacol. 27, 875–883. 
doi: 10.1089/cap.2017.0058 . 
row, J.F., 2000. The origins, patterns and implications of human 
spontaneous mutation. Nat. Rev. Genet. 1, 40–47. doi: 10.1038/ 
35049558 , 2000 1:1 . 
satlosova, K., Bogi, E., Durisova, B., Grinchii, D., Paliokha, R., 
Moravcikova, L., Lacinova, L., Jezova, D., Dremencov, E., 2021. 
Maternal immune activation in rats attenuates the excitabil- 
ity of monoamine-secreting neurons in adult offspring in a sex- 
specific way. Eur. Neuropsychopharmacol. 43, 82–91. doi: 10. 
1016/J.EURONEURO.2020.12.002 . 
aldegan-Bueno, D., Maia, L.O., Glass, M., Jutras-Aswad, D., Fis- 
cher, B., 2021. Co-exposure of cocaine and cannabinoids and its 
association with select biological, behavioural and health out- 
comes: a systematic scoping review of multi-disciplinary stud- 
ies. Eur. Neuropsychopharmacol. 51, 106–131. doi: 10.1016/J. 
EURONEURO.2021.06.002 . 
avies, C., Segre, G., Estradé, A., Radua, J., De Micheli, A., 
Provenzani, U., Oliver, D., Salazar de Pablo, G., Ramella- 
Cravaro, V., Besozzi, M., Dazzan, P., Miele, M., Caputo, G., 
Spallarossa, C., Crossland, G., Ilyas, A., Spada, G., Politi, P., 
Murray, R.M., McGuire, P., Fusar-Poli, P., 2020. Prenatal and 
perinatal risk and protective factors for psychosis: a system- 
G. Fico, V. Oliva, M. De Prisco et al. 
D
D
D
D
E
F
F
F
F
F
G
G
 
G
G  
 
G
 
H
H
H
H
H
H
J
K
K
K
K
K
K
Katic review and meta-analysis. Lancet Psychiatry 7, 399–410. 
doi: 10.1016/S2215- 0366(20)30057- 2 . 
avis, A.R., Beasley, A.D., 2009. Abortion in adolescents: epidemi- 
ology, confidentiality, and methods. Curr. Opin. Obstet. Gy- 
necol. 21, 390–395. doi: 10.1097/GCO.0B013E3283307B84 . 
enomme, M.M., Haywood, M.E., Parks, J.C., Schoolcraft, W.B., 
Katz-Jaffe, M.G., 2020. The inherited methylome landscape is 
directly altered with paternal aging and associated with off- 
spring neurodevelopmental disorders. Aging Cell 19, e13178. 
doi: 10.1111/ACEL.13178 . 
’Onofrio, B.M., Rickert, M.E., Frans, E., Kuja-Halkola, R., 
Almqvist, C., Sjölander, A., Larsson, H., Lichtenstein, P., 2014a. 
Paternal age at childbearing and offspring psychiatric and aca- 
demic morbidity. JAMA Psychiatry 71, 432–438. doi: 10.1001/ 
JAMAPSYCHIATRY.2013.4525 . 
’Onofrio, B.M., Rickert, M.E., Frans, E., Kuja-Halkola, R., 
Almqvist, C., Sjölander, A., Larsson, H., Lichtenstein, P., 2014b. 
Paternal age at childbearing and offspring psychiatric and aca- 
demic morbidity. JAMA Psychiatry 71, 432–438. doi: 10.1001/ 
jamapsychiatry.2013.4525 . 
isenberg, D.T.A., Kuzawa, C.W., 2018. The paternal age at con- 
ception effect on offspring telomere length: mechanistic, com- 
parative and adaptive perspectives. Philos. Trans. R. Soc. B 373. 
doi: 10.1098/RSTB.2016.0442 . 
ico, G., Luciano, M., Sampogna, G., Zinno, F., Steardo, L.J., Pe- 
rugi, G., Pompili, M., Tortorella, A., Volpe, U., Fiorillo, A., 
Maj, M., 2019. Validation of the brief TEMPS-M temperament 
questionnaire in a clinical Italian sample of bipolar and cy- 
clothymic patients. J. Affect. Disord. 260, 458–462. doi: 10. 
1016/j.jad.2019.09.034 . 
ountoulakis, K.N., Gonda, X., Siamouli, M., Panagiotidis, P., 
Moutou, K., Nimatoudis, I., Kasper, S., 2019. A case-control 
study of paternal and maternal age as risk factors in mood dis- 
orders. Int. J. Psychiatry Clin. Pract. 23, 90–98. doi: 10.1080/ 
13651501.2018.1519079 . 
rans, E.M., Sandin, S., Reichenberg, A., Lichtenstein, P., 
Långström, N., Hultman, C.M., 2008a. Advancing paternal age 
and bipolar disorder. Arch. Gen. Psychiatry 65, 1034–1040. 
doi: 10.1001/ARCHPSYC.65.9.1034 . 
rans, E.M., Sandin, S., Reichenberg, A., Lichtenstein, P., 
Långström, N., Hultman, C.M., 2008b. Advancing paternal age 
and bipolar disorder. Arch. Gen. Psychiatry 65, 1034–1040. 
doi: 10.1001/ARCHPSYC.65.9.1034 . 
romer, M., Pocklington, A.J., Kavanagh, D.H., Williams, H.J., 
Dwyer, S., Gormley, P., Georgieva, L., Rees, E., Palta, P., Rud- 
erfer, D.M., Carrera, N., Humphreys, I., Johnson, J.S., Rous- 
sos, P., Barker, D.D., Banks, E., Milanova, V., Grant, S.G., Han- 
non, E., Rose, S.A., Chambert, K., Mahajan, M., Scolnick, E.M., 
Moran, J.L., Kirov, G., Palotie, A., McCarroll, S.A., Holmans, P., 
Sklar, P., Owen, M.J., Purcell, S.M., O’Donovan, M.C., 2014. De 
novo mutations in schizophrenia implicate synaptic networks. 
Nature 506, 179–184. doi: 10.1038/nature12929 . 
arcia-Rizo, C., Bitanihirwe, B.K.Y., 2020. Implications of early life 
stress on fetal metabolic programming of schizophrenia: a fo- 
cus on epiphenomena underlying morbidity and early mortality. 
Prog. Neuropsychopharmacol. Biol. Psychiatry 101. doi: 10.1016/ 
J.PNPBP.2020.109910 . 
iménez, A., Pacchiarotti, I., Gil, J., Murru, A., Gomes, S.P., 
Pinzón, J.E., Anmella, G., Gómez-Ramiro, M., Verdolini, N., Va- 
lentí, M., Goikolea, J.M., Vieta, E., 2019. Adverse outcomes dur- 
ing pregnancy and major congenital malformations in infants 
of patients with bipolar and schizoaffective disorders treated 
with antiepileptic drugs: a systematic review TT – Działania 
niepo z˙ a˛dane w czasie ci a˛ z˙y i powa z˙ne wrodzone wady. Psychi-
atr. Pol. 53, 223–244. doi: 10.12740/PP/105906 . 
oldberg, S., Fruchter, E., Davidson, M., Reichenberg, A., Yoffe, R., 
Weiser, M., 2011. The relationship between risk of hospi- 72 talization for schizophrenia, SES, and cognitive functioning. 
Schizophr. Bull. 37, 664. doi: 10.1093/SCHBUL/SBR047 . 
rant, B.F. , Stinson, F.S. , Hasin, D.S. , Dawson, D.A. , Chou, S.P. ,
Ruan, W.J. , Huang, B. , 2005. Prevalence, correlates, and co- 
morbidity of bipolar I disorder and axis I and II disorders: results
from the national epidemiologic survey on alcohol and related 
conditions. J. Clin. Psychiatry 66, 1205–1215 . 
rigoroiu-Serbanescu, M., Wickramaratne, P.J., Mihailescu, R., 
Prelipceanu, D., Sima, D., Codreanu, M., Grimberg, M., El- 
ston, R.C., 2012. Paternal age effect on age of onset in bipolar 
I disorder is mediated by sex and family history. Am. J. Med.
Genet. B Neuropsychiatr. Genet. 159B, 567–579. doi: 10.1002/ 
AJMG.B.32063 . 
antsoo, L., Kornfield, S., Anguera, M.C., Epperson, C.N., 2019. 
Inflammation: a proposed intermediary between maternal stress 
and offspring neuropsychiatric risk. Biol. Psychiatry 85, 97–106. 
doi: 10.1016/J.BIOPSYCH.2018.08.018 . 
arville, D.A., 1977. Maximum likelihood approaches to variance 
component estimation and to related problems. J. Am. Stat. As- 
soc. 72, 320–338. doi: 10.1080/01621459.1977.10480998 . 
elenius, D., Jørgensen, P.M., Steinhausen, H.C., 2013. A three 
generations nation-wide population study of family load esti- 
mates in bipolar disorder with different age at onset. J. Affect. 
Disord. 150, 146–151. doi: 10.1016/J.JAD.2012.12.013 . 
erbert, T.B., Cohen, S., 1993. Stress and immunity in humans: 
a meta-analytic review. Psychosom. Med. 55, 364–379. doi: 10. 
1097/00006842- 199307000- 00004 . 
iggins, J.P.T., Thompson, S.G., Deeks, J.J., Altman, D.G., 2003. 
Measuring inconsistency in meta-analyses. BMJ 327, 557–560. 
doi: 10.1136/BMJ.327.7414.557 . 
illegers, M.H.J., Burger, H., Wals, M., Reichart, C.G., Ver- 
hulst, F.C., Nolen, W.A., Ormel, J., 2004. Impact of stressful 
life events, familial loading and their interaction on the onset 
of mood disorders: study in a high-risk cohort of adolescent off- 
spring of parents with bipolar disorder. Br. J. Psychiatry 185, 
97–101. doi: 10.1192/BJP.185.2.97 . 
acob, L., Gerhard, C., Kostev, K., Kalder, M., 2019. Association 
between induced abortion, spontaneous abortion, and infertil- 
ity, respectively, and the risk of psychiatric disorders in 57,770 
women followed in gynecological practices in Germany. J. Af- 
fect. Disord. 251, 107–113. doi: 10.1016/J.JAD.2019.03.060 . 
aye, D.K., 2008. Negotiating the transition from adolescence 
to motherhood: coping with prenatal and parenting stress in 
teenage mothers in Mulago hospital, Uganda. BMC Public Health 
8, 1–6. doi: 10.1186/1471- 2458- 8- 83/PEER- REVIEW . 
essing, L.V., 2006. Diagnostic subtypes of bipolar disorder in older 
versus younger adults. Bipolar Disord. 8, 56–64. doi: 10.1111/J. 
1399-5618.2006.00278.X . 
essing, L.V., Agerbo, E., Mortenssen, P.B., 2004. Major stressful 
life events and other risk factors for first admission with ma- 
nia. Bipolar Disord. 6, 122–129. doi: 10.1111/J.1399-5618.2004. 
00102.X . 
essing, L.v., Agerbo, E., Mortensen, P.B., 2003. Does the impact of 
major stressful life events on the risk of developing depression 
change throughout life? Psychol. Med. 33, 1177–1184. doi: 10. 
1017/S0033291703007852 . 
hachadourian, V., Zaks, N., Lin, E., Reichenberg, A., Janecka, M., 
2021. Advanced paternal age and risk of schizophrenia in off- 
spring – review of epidemiological findings and potential mech- 
anisms. Schizophr. Res. 233, 72–79. doi: 10.1016/j.schres.2021. 
06.016 . 
halfallah, O., Barbosa, S., Martinuzzi, E., Davidovic, L., 
Yolken, R., Glaichenhaus, N., 2022. Monitoring inflammation in 
psychiatry: caveats and advice. Eur. Neuropsychopharmacol. 54, 
126–135. doi: 10.1016/J.EURONEURO.2021.09.003 . 
ong, A., Frigge, M.L., Masson, G., Besenbacher, S., Sulem, P., 
Magnusson, G., Gudjonsson, S.A., Sigurdsson, A., Jonasdot- 
tir, A., Jonasdottir, A., Wong, W.S.W., Sigurdsson, G., Wal- 
European Neuropsychopharmacology 60 (2022) 55–75 
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P
Pters, G.B., Steinberg, S., Helgason, H., Thorleifsson, G., Gud- 
bjartsson, D.F., Helgason, A., Magnusson, O.T., Thorsteinsdot- 
tir, U., Stefansson, K., 2012. Rate of de novo mutations and the 
importance of father’s age to disease risk. Nature 488, 471–475. 
doi: 10.1038/NATURE11396 , 20127412 488 . 
arroya, M., Tortajada, M., Mensión, E., Pauta, M., Rodriguez- 
Revenga, L., Borrell, A., 2021. Have maternal or paternal ages 
any impact on the prenatal incidence of genomic copy number 
variants associated with fetal structural anomalies? PLoS One 
16. doi: 10.1371/JOURNAL.PONE.0253866 . 
aubenthal, J., Zlobinskaya, O., Poterlowicz, K., Baumgartner, A., 
Gdula, M.R., Fthenou, E., Keramarou, M., Hepworth, S.J., Klein- 
jans, J.C.S., van Schooten, F.J., Brunborg, G., Godschalk, R.W., 
Schmid, T.E., Anderson, D., 2012. Cigarette smoke-induced 
transgenerational alterations in genome stability in cord blood 
of human F1 offspring. FASEB J. 26, 3946–3956. doi: 10.1096/FJ. 
11-201194 . 
aurenzi, C.A., Gordon, S., Abrahams, N., du Toit, S., Brad- 
shaw, M., Brand, A., Melendez-Torres, G.J., Tomlinson, M., 
Ross, D.A., Servili, C., Carvajal-Aguirre, L., Lai, J., Dua, T., 
Fleischmann, A., Skeen, S., 2020. Psychosocial interventions 
targeting mental health in pregnant adolescents and adoles- 
cent parents: a systematic review. Reprod. Health 17, 1–15. 
doi: 10.1186/S12978- 020- 00913- Y/TABLES/4 . 
aursen, T.M., Munk-Olsen, T., Nordentoft, M., Mortensen, P.B., 
2007. A comparison of selected risk factors for unipolar depres- 
sive disorder, bipolar affective disorder, schizoaffective disor- 
der, and schizophrenia from a Danish population-based cohort. 
J. Clin. Psychiatry 68, 1673–1681. doi: 10.4088/JCP.V68N1106 . 
ehrer, D.S., Pato, M.T., Nahhas, R.W., Miller, B.R., Malaspina, D., 
Buckley, P.F., Sobell, J.L., Walsh-Messinger, J., Pato, C.N., 
Abbott, Azevedo, M.H., Bromet, E.J., Escamilla, M.A., 
Fanous, A.H., Fochtmann, L.J., Kinkead, B., Knowles, J.A., 
Macciardi, F., Macedo, A., Marder, S.R., McCarroll, S.A., 
Medeiros, H., Morley, C.P., Nicolini, H., Rakofsky, J.J., Rapa- 
port, M.H., Perkins, D.O., Sklar, P., Smoller, J.W., Vawter, M., 
Cohort Consortium, G.P., 2016. Paternal age effect: replication 
in schizophrenia with intriguing dissociation between bipolar 
with and without psychosis. Am. J. Med. Genet. B Neuropsy- 
chiatr. Genet. 171, 495–505. doi: 10.1002/AJMG.B.32334 . 
iang, C.S., Bai, Y.M., Hsu, J.W., Huang, K.L., Ko, N.Y., Yeh, T.C., 
Chu, H., te, Tsai, S.J., Chen, T.J., Chen, M.H., 2021. Asso- 
ciations of parental mental disorders and age with childhood 
mental disorders: a population-based cohort study with four 
million offspring. Eur. Child Adolesc. Psychiatry doi: 10.1007/ 
S00787- 021- 01914- 3 . 
inschooten, J.O., Verhofstad, N., Gutzkow, K., Olsen, A.K., 
Yauk, C., Oligschläger, Y., Brunborg, G., van Schooten, F.J., God- 
schalk, R.W.L., 2013. Paternal lifestyle as a potential source of 
germline mutations transmitted to offspring. FASEB J. 27, 2873–
2879. doi: 10.1096/FJ.13-227694 . 
ai, C.T., Kucik, J.E., Isenburg, J., Feldkamp, M.L., Marengo, L.K., 
Bugenske, E.M., Thorpe, P.G., Jackson, J.M., Correa, A., 
Rickard, R., Alverson, C.J., Kirby, R.S., 2013. Selected birth 
defects data from population-based birth defects surveillance 
programs in the United States, 2006 to 2010: featuring trisomy 
conditions. Birth Defects Res. A Clin. Mol. Teratol. 97 (709). 
doi: 10.1002/BDRA.23198 . 
alaspina, D., 2001a. Paternal factors and schizophrenia risk: de 
novo mutations and imprinting. Schizophr. Bull. 27, 379–393. 
doi: 10.1093/oxfordjournals.schbul.a006882 . 
alaspina, D., Gilman, C., Kranz, T.M., 2015. Paternal age and men- 
tal health of offspring. Fertil. Steril. 103, 1392–1396. doi: 10. 
1016/j.fertnstert.2015.04.015 . 
arangoni, C., Hernandez, M., Faedda, G.L., 2016. The role of en- 
vironmental exposures as risk factors for bipolar disorder: a sys- 
tematic review of longitudinal studies. J. Affect. Disord. 193, 
165–174. doi: 10.1016/J.JAD.2015.12.055 . 73 cGrath, J.J., Petersen, L., Agerbo, E., Mors, O., Mortensen, P.B., 
Pedersen, C.B., 2014. A comprehensive assessment of parental 
age and psychiatric disorders. JAMA Psychiatry 71, 301–309. 
doi: 10.1001/JAMAPSYCHIATRY.2013.4081 . 
cGuffin, P., Rijsdijk, F., Andrew, M., Sham, P., Katz, R., Cardno, A.,
2003. The heritability of bipolar affective disorder and the ge- 
netic relationship to unipolar depression. Arch. Gen. Psychiatry 
60, 497–502. doi: 10.1001/ARCHPSYC.60.5.497 . 
enezes, P.R., Lewis, G., Rasmussen, F., Zammit, S., Sipos, A., Har- 
rison, G.L., Tynelius, P., Gunnell, D., 2010. Paternal and ma- 
ternal ages at conception and risk of bipolar affective disor- 
der in their offspring. Psychol. Med. 40, 477–485. doi: 10.1017/ 
S003329170999064X . 
esman, E., Nolen, W.A., Reichart, C.G., Wals, M., Hil- 
legers, M.H.J., 2013. The dutch bipolar offspring study: 12-year 
follow-up. Am. J. Psychiatry 170, 542–549. doi: 10.1176/APPI. 
AJP.2012.12030401/ASSET/IMAGES/LARGE/542F2.JPEG . 
iller, B., Messias, E., Miettunen, J., Alaräisänen, A., 
Järvelin, M.R., Koponen, H., Räsänen, P., Isohanni, M., 
Kirkpatrick, B., 2011. Meta-analysis of paternal age and 
schizophrenia risk in male versus female offspring. Schizophr. 
Bull. 37, 1039–1047. doi: 10.1093/SCHBUL/SBQ011 . 
ills, M., Rindfuss, R.R., McDonald, P., te Velde, E., 2011. Why 
do people postpone parenthood? Reasons and social policy in- 
centives. Hum. Reprod. Update 17, 848. doi: 10.1093/HUMUPD/ 
DMR026 . 
jajou, O.T., Cawthon, R.M., Damcott, C.M., Wu, S.H., Ott, S., 
Garant, M.J., Blackburn, E.H., Mitchell, B.D., Shuldiner, A.R., 
Hsueh, W.C., 2007. Telomere length is paternally inherited and 
is associated with parental lifespan. Proc. Natl. Acad. Sci. USA 
104, 12135. doi: 10.1073/PNAS.0702703104 . 
ldereid, N.B., Wennerholm, U.B., Pinborg, A., Loft, A., 
Laivuori, H., Petzold, M., Romundstad, L.B., Söderström- 
Anttila, V., Bergh, C., 2018. The effect of paternal factors on 
perinatal and paediatric outcomes: a systematic review and 
meta-analysis. Hum. Reprod. Update 24, 320–389. doi: 10.1093/ 
HUMUPD/DMY005 . 
acchiarotti, I., Bond, D.J., Baldessarini, R.J., Nolen, W.A., 
Grunze, H., Licht, R.W., Post, R.M., Berk, M., Goodwin, G.M., 
Sachs, G.S., Tondo, L., Findling, R.L., Youngstrom, E.A., To- 
hen, M., Undurraga, J., González-Pinto, A., Goldberg, J.F., 
Yildiz, A., Altshuler, L.L., Calabrese, J.R., Mitchell, P.B., 
Thase, M.E., Koukopoulos, A., Colom, F., Frye, M.A., Malhi, G.S., 
Fountoulakis, K.N., Vázquez, G., Perlis, R.H., Ketter, T.A., Cas- 
sidy, F., Akiskal, H., Azorin, J.-M., Valentí, M., Mazzei, D.H., 
Lafer, B., Kato, T., Mazzarini, L., Martínez-Aran, A., Parker, G., 
Souery, D., Ozerdem, A., McElroy, S.L., Girardi, P., Bauer, M., 
Yatham, L.N., Zarate, C.A., Nierenberg, A.A., Birmaher, B., 
Kanba, S., El-Mallakh, R.S., Serretti, A., Rihmer, Z., Young, A.H., 
Kotzalidis, G.D., MacQueen, G.M., Bowden, C.L., Ghaemi, S.N., 
Lopez-Jaramillo, C., Rybakowski, J., Ha, K., Perugi, G., 
Kasper, S., Amsterdam, J.D., Hirschfeld, R.M., Kapczinski, F., 
Vieta, E., 2013. The international society for bipolar disorders 
(ISBD) task force report on antidepressant use in bipolar disor- 
ders. Am. J. Psychiatry 170, 1249–1262. doi: 10.1176/appi.ajp. 
2013.13020185 . 
acheco, A.L.D., de Melo, I.S., de Souza, F.M.A., Nicácio, D.C.S.P., 
Freitas-Santos, J., Oliveira dos Santos, Y.M., Costa, M., de, A., 
Cavalcante, C., de, M.B., Gomes dos Santos Neto, J., Gi- 
taí, D.L.G., Sabino-Silva, R., Torres de Miranda, C., Bor- 
bely, A.U., Duzzioni, M., Shetty, A.K., de Castro, O.W., 
2021. Maternal crack cocaine use in rats leads to depressive- 
and anxiety-like behavior, memory impairment, and increased 
seizure susceptibility in the offspring. Eur. Neuropsychopharma- 
col. 44, 34–50. doi: 10.1016/J.EURONEURO.2020.12.011 . 
age, M.J., McKenzie, J.E., Bossuyt, P.M., Boutron, I., Hoff- 
mann, T.C., Mulrow, C.D., Shamseer, L., Tetzlaff, J.M., Akl, E.A., 
Brennan, S.E., Chou, R., Glanville, J., Grimshaw, J.M., Hrób- 
G. Fico, V. Oliva, M. De Prisco et al. 
P
P
P
P
R
R
R
S
S
S
S
S
S
S
S
S
S
S
T
T
T
V
V
V
V
V
W
W  
W
W  jartsson, A., Lalu, M.M., Li, T., Loder, E.W., Mayo-Wilson, E., 
McDonald, S., McGuinness, L.A., Stewart, L.A., Thomas, J., 
Tricco, A.C., Welch, V.A., Whiting, P., Moher, D., 2021. The 
PRISMA 2020 statement: an updated guideline for reporting sys- 
tematic reviews. BMJ 372. doi: 10.1136/BMJ.N71 . 
olderman, T.J.C., Benyamin, B., de Leeuw, C.A., Sullivan, P.F., van 
Bochoven, A., Visscher, P.M., Posthuma, D., 2015. Meta-analysis 
of the heritability of human traits based on fifty years of twin 
studies. Nat. Genet. 47, 702–709. doi: 10.1038/NG.3285 . 
olga, N., de Barros, P.M.F., Farhat, L.C., de Almeida, K.M., 
Bloch, M.H., Lafer, B., 2022. Parental age and the risk of bipolar 
disorder in the offspring: a systematic review and meta-analysis. 
Acta Psychiatr. Scand. doi: 10.1111/ACPS.13418 . 
owell, T.R., Dima, D., Frangou, S., Breen, G., 2018. Telomere 
length and bipolar disorder. Neuropsychopharmacology 43, 445. 
doi: 10.1038/NPP.2017.125 . 
reisig, M., Strippoli, M.P.F., Castelao, E., Merikangas, K.R., 
Gholam-Rezaee, M., Marquet, P., Aubry, J.M., Vandeleur, C.L., 
2016. The specificity of the familial aggregation of early-onset 
bipolar disorder: a controlled 10-year follow-up study of off- 
spring of parents with mood disorders. J. Affect. Disord. 190, 
26–33. doi: 10.1016/J.JAD.2015.10.005 . 
eichenberg, A., Gross, R., Weiser, M., Bresnahan, M., Silver- 
man, J., Harlap, S., Rabinowitz, J., Shulman, C., Malaspina, D., 
Lubin, G., Knobler, H.Y., Davidson, M., Susser, E., 2006. Advanc- 
ing paternal age and autism. Arch. Gen. Psychiatry 63, 1026–
1032. doi: 10.1001/ARCHPSYC.63.9.1026 . 
eijneveld, S.A., 2003. Age in epidemiological analysis. J. Epi- 
demiol. Community Health 57, 397. doi: 10.1136/JECH.57.6. 
397 , –397 . 
Studio Team, 2020. RStudio: Integrated Development for R. RStu- 
dio, PBC, Boston, MA URL http://www.rstudio.com/ . 
chmidt, C.O., Kohlmann, T., 2008. When to use the odds ratio or 
the relative risk? Int. J. Public Health 53, 165–167. doi: 10.1007/ 
S00038- 008- 7068- 3 , 20083 53 . 
eidman, L.J., Cherkerzian, S., Goldstein, J.M., Agnew-Blais, J., 
Tsuang, M.T., Buka, S.L., 2013. Neuropsychological perfor- 
mance and family history in children at age 7 who develop 
adult schizophrenia or bipolar psychosis in the New Eng- 
land family studies. Psychol. Med. 43, 119–131. doi: 10.1017/ 
S0033291712000773 . 
erati, M., Bertino, V., Malerba, M.R., Mucci, F., Barkin, J.L., 
Grassi, S., Altamura, A.C., Buoli, M., 2020. Obstetric compli- 
cations and subsequent risk of mood disorders for offspring in 
adulthood: a comprehensive overview. Nord. J. Psychiatry 74, 
470–478. doi: 10.1080/08039488.2020.1751878 . 
halev, I., Moffitt, T.E., Sugden, K., Williams, B., Houts, R.M., 
Danese, A., Mill, J., Arseneault, L., Caspi, A., 2013. Exposure 
to violence during childhood is associated with telomere erosion 
from 5 to 10 years of age: a longitudinal study. Mol. Psychiatry 
18, 576–581. doi: 10.1038/MP.2012.32 . 
hi, Q., Ko, E., Barclay, L., Hoang, T., Rademaker, A., Martin, R., 
2001. Cigarette smoking and aneuploidy in human sperm. Mol. 
Reprod. Dev 59, 417–421. doi: 10.1002/MRD.1048 . 
lagboom, P.E. , Droog, S. , Boomsma, D.I. , 1994. Genetic determi- 
nation of telomere size in humans: a twin study of three age 
groups. Am. J. Hum. Genet. 55, 876 . 
olé, E., Roca, A., Torres, A., Hernández, A.S., Fernández, N., 
Díaz, C.N., Vieta, E., Garcia-Esteve, L., 2020. Obstetric com- 
plications in bipolar disorder: psychiatric factors and the risk 
of caesarean section. Eur. Neuropsychopharmacol. 32, 47–55. 
doi: 10.1016/J.EURONEURO.2019.12.115 . 
tang, A, 2010. Critical evaluation of the Newcastle-Ottawa scale 
for the assessment of the quality of nonrandomized studies in 
meta-analyses. Eur J Epidemiol 25 (9), 603–605. doi: 10.1007/ 
s10654- 010- 9491- z , Epub 2010 Jul 22. PMID: 20652370 . 
teiner, B., Masood, R., Rufibach, K., Niedrist, D., Kundert, O., 
Riegel, M., Schinzel, A., 2014. An unexpected finding: younger 74 fathers have a higher risk for offspring with chromosomal ane- 
uploidies. Eur. J. Hum. Genet. 23 (4 23), 466–472. doi: 10.1038/ 
ejhg.2014.122 , 2015 . 
troup, DF, Berlin, JA, Morton, SC, Olkin, I, Williamson, GD, Ren- 
nie, D, Moher, D, Becker, BJ, Sipe, TA, Thacker, SB, 2000 Apr 
19. Meta-analysis of observational studies in epidemiology: a 
proposal for reporting. Meta-analysis Of Observational Stud- 
ies in Epidemiology (MOOSE) group. JAMA 283 (15), 2008–2012. 
doi: 10.1001/jama.283.15.2008 , PMID: 10789670 . 
ujan, A.C., O’Reilly, L.M., Rickert, M.E., Larsson, H., Lichten- 
stein, P., Oberg, A.S., D’Onofrio, B.M., 2022. A nation-wide 
swedish cohort study on early maternal age at first childbirth 
and risk for offspring deaths, accidents, and suicide attempts. 
Behav. Genet. 52, 38–47. doi: 10.1007/S10519- 021- 10091- 7 . 
alati, A., Bao, Y., Kaufman, J., Shen, L., Schaefer, C.A., 
Brown, A.S., 2013. Maternal smoking during pregnancy and bipo- 
lar disorder in offspring. Am. J. Psychiatry 170, 1178–1185. 
doi: 10.1176/APPI.AJP.2013.12121500 . 
aylor, J.L., Debost, J.C.P.G., Morton, S.U., Wigdor, E.M., 
Heyne, H.O., Lal, D., Howrigan, D.P., Bloemendal, A., 
Larsen, J.T., Kosmicki, J.A., Weiner, D.J., Homsy, J., Sei- 
dman, J.G., Seidman, C.E., Agerbo, E., McGrath, J.J., 
Mortensen, P.B., Petersen, L., Daly, M.J., Robinson, E.B., 2019. 
Paternal-age-related de novo mutations and risk for five disor- 
ders. Nat. Commun. 10. doi: 10.1038/S41467- 019- 11039- 6 . 
hompson, J.A., 2019. Disentangling the roles of maternal and pa- 
ternal age on birth prevalence of down syndrome and other 
chromosomal disorders using a Bayesian modeling approach. 
BMC Med. Res. Method 19. doi: 10.1186/S12874- 019- 0720- 1 . 
aldes, A.M., Andrew, T., Gardner, J.P., Kimura, M., Oelsner, E., 
Cherkas, L.F., Aviv, A., Spector, T.D., 2005. Obesity, cigarette 
smoking, and telomere length in women. Lancet 366, 662–664. 
doi: 10.1016/S0140- 6736(05)66630- 5 . 
edel Kessing, L., Ziersen, S.C., Andersen, P.K., Vinberg, M., 2021. 
A nationwide population-based longitudinal study mapping psy- 
chiatric disorders during lifetime in siblings to patients with 
bipolar disorder. Acta Psychiatr. Scand. 143, 284–293. doi: 10. 
1111/ACPS.13263 . 
ieta, E., 2014. Antidepressants in bipolar I disorder: never as 
monotherapy. Am. J. Psychiatry doi: 10.1176/appi.ajp.2014. 
14070826 . 
iechtbauer, W, 2010. Conducting meta-analyses in R with the 
metafor package. Journal of Statistical Software 36 (3), 1–48. 
doi: 10.18637/jss.v036.i03 . 
ervoort, I, Delger, C, Soubry, A, 2022. A multifactorial model 
for the etiology of neuropsychiatric disorders: the role of ad- 
vanced paternal age. Pediatr Res. 91 (4), 757–770. doi: 10.1038/ 
s41390- 021- 01435- 4 , Epub 2021 Mar 5. PMID: 33674740 . 
aldenström, U., 2016. Postponing parenthood to advanced age. 
Ups. J. Med. Sci. 121, 235–243. doi: 10.1080/03009734.2016. 
1201553 . 
ang, S.H., Hsiao, P.C., Yeh, L.L., Liu, C.M., Liu, C.C., Hwang, T.J.,
Hsieh, M.H., Chien, Y.L., Lin, Y.T., Huang, Y.T., Chen, C.Y., Chan- 
dler, S.D., Faraone, S.v., Neale, B., Glatt, S.J., Tsuang, M.T., 
Hwu, H.G., Chen, W.J., 2019. Advanced paternal age and early 
onset of schizophrenia in sporadic cases: not confounded by 
parental polygenic risk for schizophrenia. Biol. Psychiatry 86, 
56–64. doi: 10.1016/J.BIOPSYCH.2019.01.023 . 
eiser, M., Fenchel, D., Frenkel, O., Fruchter, E., Burshtein, S., 
Yehuda, A., Yoffe, R., Bergman-Levi, T., Reichenberg, A., 
Davidson, M., Sandin, S., 2020a. Understanding the associa- 
tion between advanced paternal age and schizophrenia and 
bipolar disorder. Psychol. Med. 50, 431–437. doi: 10.1017/ 
S0033291719000242 . 
u, S., Wu, F., Ding, Y., Hou, J., Bi, J., Zhang, Z., 2017. Advanced
parental age and autism risk in children: a systematic review 
and meta-analysis. Acta Psychiatr. Scand. 135, 29–41. doi: 10. 
1111/ACPS.12666 . 
European Neuropsychopharmacology 60 (2022) 55–75 
Z
Z
Zammit, S., Allebeck, P., Dalman, C., Lundberg, I., Hemming- 
son, T., Owen, M.J., Lewis, G., 2003. Paternal age and risk for 
schizophrenia. Br. J. Psychiatry 183, 405–408. doi: 10.1192/BJP. 
183.5.405 . 
hang, J., Yu, K.F., 1998. What’s the relative risk?: A method of 
correcting the odds ratio in cohort studies of common outcomes. 
JAMA 280, 1690–1691. doi: 10.1001/JAMA.280.19.1690 . 75 hang, T., Sidorchuk, A., Sevilla-Cermeño, L., Vilaplana-Pérez, A., 
Chang, Z., Larsson, H., Mataix-Cols, D., Fernández De La 
Cruz, L., 2019. Association of cesarean delivery with risk 
of neurodevelopmental and psychiatric disorders in the off- 
spring: a systematic review and meta-analysis. JAMA Netw. Open 
2, e1910236. doi: 10.1001/JAMANETWORKOPEN.2019.10236 , –
e1910236 .