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. Author manuscript; available in PMC: 2026 Jan 31.
Published in final edited form as: Am J Med Genet B Neuropsychiatr Genet. 2015 Jul 16;171(4):495–505. doi: 10.1002/ajmg.b.32334

Paternal Age Effect: Replication in Schizophrenia with Intriguing Dissociation Between Bipolar with and without Psychosis

Douglas S Lehrer 1,2,*, Michele T Pato 3,4, Ramzi W Nahhas 1,5, Brian R Miller 6, Dolores Malaspina 7, Peter F Buckley 6,8, Janet L Sobell 4, Julie Walsh-Messinger 9; Genomic Psychiatry Cohort Consortium, Carlos N Pato 3,4
PMCID: PMC12856734  NIHMSID: NIHMS2138869  PMID: 26183902

Abstract

Advanced paternal age (APA) is a risk factor for schizophrenia (Sz) and bipolar disorder (BP). Putative mechanisms include heritable genetic factors, de novo mutations, and epigenetic mechanisms. Few studies have explored phenotypic features associated with APA. The Genomic Psychiatry Cohort established a clinically characterized repository of genomic samples from subjects with a Sz-BP diagnosis or unaffected controls, 12,975 with parental age information. We estimated relative risk ratios for Sz, schizoaffective depressed and bipolar types (SA-D, SA-B), and BP with and without history of psychotic features (PF) relative to the control group, comparing each paternal age group to the reference group 20–24 years. All tests were two-sided with adjustment for multiple comparisons. Subjects with fathers age 45+ had significantly higher risk for all diagnoses except for BP w/o PF. APA also bore no significant relation to family psychiatric history. In conclusion, we replicated APA as a risk factor for Sz. To our knowledge, this is the first published report of APA in a BP sample stratified by psychosis history, extending this association only in BP w/PF. This suggests that phenotypic expression of the APA effect in Sz-BP spectrum is psychosis, per se, rather than other aspects of these complex disorders. The lack of a significant relationship between paternal age and familial disease patterns suggests that underlying mechanisms of the paternal age effect may involve a complex interaction of heritable and non-heritable factors. The authors discuss implications and testable hypotheses, starting with a focus on genetic mechanisms and endophenotypic expressions of dopaminergic function.

Keywords: paternal age, schizophrenia, bipolar, psychosis, phenotype

INTRODUCTION

An increasing scientific literature implicates advanced paternal age as a risk factor for many subsequent health disturbances, neuropsychiatric, and otherwise. Advanced paternal age was first explicitly identified in association with schizophrenia in 1958 by Johanson [Johanson, 1958], though by discussing it in the “home background” rather than “hereditary conditions” section of the study report, he appears to have viewed this factor as an environmental influence. Numerous subsequent studies predominantly utilizing population registry databases, including those compiled in the United Kingdom [Hare and Moran, 1979], Israel [Malaspina et al., 2001], the United States [Brown et al., 2002; Torrey et al., 2009], Sweden [Zammit et al., 2003; Sipos et al., 2004; Frans et al., 2011; D’Onofrio et al., 2014], and Denmark [Byrne et al., 2003] have clearly established paternal age as a risk factor for schizophrenia. Two Scandinavian studies demonstrated an association between advanced paternal age and schizophrenia, but after controlling for age of first paternity, these authors concluded that the apparent association is due to delayed fatherhood [Petersen et al., 2011; Ek et al., 2014]. Two early case control studies failed to demonstrate the effect, though the larger, earlier study used siblings as controls [Granville-Grossman, 1966] while the other reported a rather small sample (120 cases, 176 controls) [Bertranpetit and Fañanás, 1993]. A Finnish birth cohort study also did not find a significant association between paternal age and non-affective psychosis [Miller et al., 2011a]. However, several meta-analytic studies further confirmed the paternal age effect in schizophrenia [Wohl and Gorwood, 2007; Torrey et al., 2009; Hubert et al., 2011; Matheson et al., 2011; Miller et al., 2011a].

Despite the repeated replication of a paternal age effect in schizophrenia, very little has been characterized concerning the clinical features of schizophrenia associated with paternal age. Malaspina and co-workers have contributed much of what is known about the clinical characteristics of paternal age-related schizophrenia (PARS), including loss of sex differences in age of onset and negative symptom burden, off-medication symptom severity (PARS > non-PARS), higher verbal IQ, and greater verbalminus-performance intelligence differences [Malaspina et al., 2002; Rosenfield et al., 2010; Lee et al., 2011]. Affected offspring of older fathers also appeared to display poorer social functioning than their younger-parent counterparts [Weiser et al., 2008]. The Consortium on the Genetics of Schizophrenia (COGS) reported that patients with older fathers appeared to have diminished performance on two tasks within the COGS endophenotype assessment battery, including a test for verbal memory and the Identical Pairs version of the Continuous Performance Test, though the significance of these initial observations did not survive a statistical correction for multiple comparisons [Tsuang et al., 2014].

The most commonly proposed mechanism for the effect of paternal age on human disease risk is de novo genetic mutations in the aging paternal germ line. Kong and co-workers, estimated a doubling of paternal mutations every 16.5 years, an effect potentially amplified by skew towards propagation of paternally derived mutations, a phenomenon known as “selfish spermatogonial selection” [Kong et al., 2012; Goriely et al., 2013]. While other mechanisms have also been proposed, such as longer telomere length [Malaspina et al., 2014], the de novo mutation hypothesis remains most prominent.

The literature regarding paternal age and schizophrenia is mixed regarding evidence for de novo mutations. Petersen and colleagues [Petersen et al., 2011] reported that paternal age at birth of first child, but not later born children, was associated with schizophrenia. They termed this the “selection into late fatherhood” hypothesis which argued against de novo mutations. Miller and co-workers [Miller et al., 2011b] also found in both the general population and in patients with schizophrenia, that advanced paternal age was associated with increased risk of a maternal history of psychosis (i.e., older dads more likely to have children with psychotic mothers). In contrast, Malaspina and co-workers [Malaspina et al., 2002] found older mean paternal age in a group of sporadic (versus familial) cases. And D’Onofrio and co-workers [D’Onofrio et al., 2014], using a unique case-sibling design, also found strong evidence supporting the de novo mutation hypothesis. So the question of whether paternal age is a genetic or environmental risk factor, or a combination of both, remains unsolved. In some cases, paternal age could be associated with mutations while other instances may have to do with environmental or other effects of delayed fatherhood.

In contrast to the situation with schizophrenia, the question of a paternal age effect on bipolar disorder is far less conclusive. Study results have been inconsistent with some identifying a paternal age effect [Frans et al., 2008; Chudal et al., 2014; D’Onofrio et al., 2014], while others either showed an inconsistent relationship [Laursen et al., 2007] or failed to demonstrate any association [Buizer-Voskamp et al., 2011; Brown et al., 2013]. Notably, in no case did any of these investigators report analyses stratified by presence or absence of a history of psychotic features.

Herein, we will report analyses of data obtained in the Genomic Psychiatry Cohort (GPC) study. This large clinical and demographic dataset permits examination of paternal age effects in subjects across the schizophrenia-bipolar spectrum, including bipolar subjects with and without a history of psychotic episodes. We hypothesized that older paternal age would be associated with increased risk of schizophrenia and bipolar disorders. Moreover, on the basis of the de novo mutation hypothesis, we hypothesized that patients with older fathers would be less likely to have identified schizophrenia or other psychiatric illness within their families.

MATERIALS AND METHODS

The Genomic Psychiatry Cohort (GPC) represents the efforts of a multi-institutional partnership under the direction of the University of Southern California to assemble a historically large cohort of people with bipolar-schizophrenia spectrum disorders (“cases”) along with first-degree relatives and unaffected controls, from whom we obtained venous blood, a screening questionnaire and, in patients and family members, a semi-structured clinical interview called the Diagnostic Interview for Psychotic and Affective Disorders (DI-PAD). The DI-PAD uses questions developed for the Diagnostic Interview for Genetic Studies (DIGS) [Nurnberger et al., 1994], and links to the Operational Criteria Checklist for Psychotic Illness (OPCRIT) algorithm to derive psychiatric diagnoses. The DI-PAD has distinct modules containing detailed questions regarding lifetime history of depressive, manic, and psychotic symptoms, as well as a module in which the rater records observable behaviors indicative of active psychopathology. The OPCRIT is a 90-item checklist and computerized diagnostic algorithm [McGuffin et al., 1991; Williams et al., 1996], and has been successfully used in the genetic analysis of phenotypic heterogeneity in both schizophrenia [Fanous et al., 2005] and bipolar disorder [Schulze et al., 2005]. OPCRIT diagnoses can be based on a variety of different systems. All GPC OPCRIT diagnoses are based on DSM-IV-TR criteria [American Psychiatric Association, 2000]. The DI-PAD modules provide a consistent method to collect required data from patient and informant interviews and through record review, and form the basis for assignment of DSM-IV-TR diagnoses including schizophrenia, schizoaffective disorder, bipolar disorder (with or without history of psychotic features). The DI-PAD contains two questions regarding family history: one a query about family history of schizophrenia and the other asking about family history of disorders “other than schizophrenia.” Both of these questions pertain to first and second degree relatives. The DI-PAD does not specifically ask subjects about a family history of other specific syndromes or diagnoses such as mania or bipolar disorder. Raters used their discretion regarding the need to consult collateral information sources (family members, treating clinicians, residential facility staff, health records) in the completion of the DI-PAD, based upon the observed cogency and completeness of account by the subject. As such, the time needed per DI-PAD ranged widely from about 30 min to a couple of hours.

The screening questionnaire collects information about psychiatric and general medical history as well as autobiographical and family information. Individuals reporting any lifetime symptoms indicative of psychosis or mania in self or first-degree family members were excluded as control participants. The questionnaire is a compilation of questions from well-validated interviews and includes 32 questions and screens for mania, psychosis, depression, anxiety disorder, alcohol, nicotine, and other substance use history. In addition, there is a section on demographic information (i.e., age, gender, and self-identifying race and ethnicity) and a section on medical conditions and disorders including head trauma and seizure history. The questionnaire is the sole source for information regarding the years of birth of each parent, if known. This information was generally obtained directly from subjects and was recorded without external validation by another source.

Blood samples were forwarded to an NIMH-administered repository presently located at Rutgers University, at which enduring lymphocytic cell lines were created. All aspects of this study were done in compliance with the Code of Ethics of the World Medical Association (Declaration of Helsinki) and pursuant to the standards and specific approvals established by each sites’ Institutional Review Board. Additional information regarding the GPC may be found in Pato et al. [2013]. The GPC continues to grow, though at the time of the present analyses approximately 33,000 subjects comprised the cohort.

The present study utilized GPC data from cases across the bipolar-schizophrenia diagnostic spectrum as well as unaffected controls. First-degree family members were not included. We obtained subject data for whom paternal birth year information existed. Parental age information was generally self-reported by subjects. We excluded subjects with paternal age reported to be <13 years. All participants were age ≥18 years. A total of 12,975 subjects met inclusion criteria.

Using this retrospective cohort, our primary analysis was a test of the null hypothesis that paternal age is unrelated to the risk of having bipolar disorder with psychotic features, bipolar disorder without psychotic features, or schizophrenia (all subtypes as well as schizoaffective disorder). In secondary analyses, we tested the null hypotheses that, within cases, paternal age is unrelated to family history of schizophrenia, and unrelated to family history of psychiatric disorders other than schizophrenia. The secondary analyses were conducted separately for participants with bipolar disorder (with and without psychosis combined) and schizophrenia (and controls were excluded as they all had no family history by design).

Paternal age was categorized as <20 years, 20–24 (reference group), 25–29, 30–34, 35–39, 40–44, and 45+ years. For the primary analysis, multinomial logistic regression was used to estimate the relative risk ratio (RRR) for each of the three disorder types relative to the control group, comparing each paternal age group to the reference group 20–24 years. This group was chosen a priori as the reference group based on previous research indicating a J-shaped relationship between paternal age and risk of schizophrenia, with both younger and older paternal age associated with greater risk [Miller et al., 2011]. RRR >1 for a given age group and psychiatric disorder indicates a greater risk of having that disorder relative to the reference age group. For the secondary analyses, binary logistic regression was used to estimate an odds ratio (OR) representing the odds of “no family history” in each paternal age group relative to the reference age group. An OR >1 for a given age group indicates a greater odds of no family history relative to the reference age group.

The analyses were adjusted for the following covariates: difference between paternal and maternal ages, sex, race, and age. Due to sparse categories, race was grouped into four levels: (i) African American or black; (ii) American Indian/Alaskan Native, Asian, or Native Hawaiian/Pacific Islander; (iii) More than one race, other, or unknown; and (iv) white. Analyses were not adjusted for family history of psychiatric disorder; in the primary analysis, controls had no family history by design and, in the secondary analysis family history was the outcome. Covariates were included only if statistically significant.

Data analysis was carried out using PROC LOGISTIC in SAS 9.3 [SAS Institute, Inc., 2010]. All tests were two-sided at the 0.05 level of significance. The Holm–Bonferroni adjustment for multiple comparisons [Holm, 1979] was used to adjust for multiplicity of testing between paternal age groups.

RESULTS

The characteristics of the study sample are summarized in Table I.

TABLE I.

Sample Characteristics—Mean (SD) or N (%) (Total N = 12,975)

Variable Level Control
N = 7658 (59.0%)		 Bipolar w/psychosis
N = 941 (7.3%)		 Bipolar w/o psychosis
N = 434 (3.3%)		 Schizophrenia and schizoaffective
N = 3942 (30.4%)
Sex Female 4542 (59.3%) 489 (52.0%) 277 (63.8%) 1313 (33.3%)
Male 3116 (40.7%) 452 (48.0%) 157 (36.2%) 2629 (66.7%)
Race African American or Black 1020 (13.3%) 133 (14.1%) 46 (10.6%) 1192 (30.2%)
American Indian/Alaskan Native 75 (1.0%) 6 (0.6%) 3 (0.7%) 64 (1.6%)
Asian 598 (7.8%) 21 (2.2%) 7 (1.6%) 94 (2.4%)
More Than One Race 474 (6.2%) 105 (11.2%) 32 (7.4%) 310 (7.9%)
Native Hawaiian/Pacific Islander 49 (0.6%) 3 (0.3%) 1 (0.2%) 11 (0.3%)
Other/Unknown 749 (9.8%) 62 (6.6%) 31 (7.1%) 201 (5.1%)
White 4693 (61.3%) 611 (64.9%) 314 (72.4%) 2070 (52.5%)
Family history 0 (0%) 681 (72.4%) 311 (71.7%) 2261 (57.4%)
Age 37.6 (14.6) 42.8 (12.6) 42.4 (13.7) 43.5 (12.6)
Paternal Age 30.3 (7.5) 31.0 (8.2) 30.5 (7.4) 30.7 (8.3)
Maternal Agea 27.5 (6.4) 28.1 (6.6) 28.0 (6.6) 27.5 (6.8)
Paternal age—maternal agea 2.8 (5.0) 3.0 (5.6) 2.4 (4.7) 3.0 (5.7)
Age of onsetb — — 21.9 (9.0) 22.0 (9.8) 22.0 (7.7)
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a

There were 321, 18, 63, and 322 participants with unknown maternal age in the control and three disorder groups, respectively (including maternal ages reported to be <13 years or ≥55 years, which were treated as unknown).

b

Age of onset is not defined for the control group, and there were 1, 3, and 25 participants with unknown age of onset in the three disorder groups, respectively.

For the primary analysis, age, sex, race, and paternal age were significantly associated with the risk of psychiatric disorder. While there were some significant interaction terms (age × race and sex × race), these did not impact the paternal age effect results. For clarity, results without interaction terms are presented here. However, full results are provided in Supplementary Material (Table SI).

Relative risk ratios for the primary analysis are shown in Table II. Older participants had significantly higher risk, indicating a secular trend towards lower risk of psychiatric disorder (RRRs ranging from 1.538 to 1.845 for a 20-year difference in age). Males were significantly more likely than females to have bipolar disorder with psychotic features (RRR = 1.365, 95%CI = 1.190, 1.565) and schizophrenia (RRR = 2.879, 95%CI = 2.649, 3.130). Black participants were significantly more likely to have schizophrenia compared to white participants (RRR = 2.687, 95%CI = 2.421, 2.984), and American Indian/Alaskan Native, Asian, or Native Hawaiian/Pacific Islanders were significantly less likely to have each of the three disorders compared to white participants (RRRs ranging from 0.263 to 0.640). After controlling for multiple comparisons, participants with fathers age 45+ years had significantly higher risk than those with fathers age 20–24 years of having bipolar disorder with psychotic features (RRR = 1.939, 95%CI = 1.411, 2.643) and schizophrenia (RRR = 1.442, 95%CI = 1.172, 1.773), but not bipolar disorder without psychotic features (RRR = 0.934, 95%CI = 0.536, 1.543).

TABLE II.

Relative Risk Ratios (RRR) and 95% Confidence Intervals (CI) Estimated Via Multinomial Logistic Regression for Primary Analysis

Effect Group 1 Group 2 Bipolar w/psychosis
Versus control		 Bipolar w/o psychosis
Versus control		 Schizophrenia and
schizoaffective
Versus control		 P-value
Age +20y 1.668 (1.512, 1.840) 1.538 (1.340, 1.765) 1.845 (1.738, 1.959) <0.0001
Sex Male Female 1.365 (1.190, 1.565) 0.847 (0.691, 1.035) 2.879 (2.649, 3.130) <0.0001
Race African American or Black White 1.043 (0.849, 1.273) 0.718 (0.515, 0.978) 2.687 (2.421, 2.984) <0.0001
American Indian/Alaskan Native, Asian, or Native Hawaiian/Pacific Islander White 0.370 (0.249, 0.531) 0.263 (0.134, 0.459) 0.640 (0.532, 0.767)
More than one race, other, or unknown White 1.206 (0.999, 1.451) 0.878 (0.657, 1.156) 1.121 (0.991, 1.265)
Age of father <20 years 20–24 years 0.933 (0.648, 1.320) 0.440 (0.220, 0.798) 0.871 (0.711, 1.066) 0.0002
25–29 years 20–24 years 1.035 (0.837, 1.284) 0.879 (0.660, 1.174) 0.945 (0.833, 1.072)
30–34 years 20–24 years 1.123 (0.904, 1.397) 0.795 (0.587, 1.077) 1.005 (0.883, 1.144)
35–39 years 20–24 years 1.033 (0.809, 1.317) 0.988 (0.718, 1.359) 1.038 (0.900, 1.196)
40–44 years 20–24 years 1.051 (0.764, 1.432) 0.920 (0.593, 1.391) 1.223 (1.022, 1.462)
45+ years 20–24 years * 1.939 (1.411, 2.643) 0.934 (0.536, 1.543) * 1.442 (1.172, 1.773)
Sample size Control Bipolar w/psychosis Bipolar w/o psychosis Schizophrenia and
schizoaffective		 Total
<20 years 391 44 11 218 664
20–24 years 1334 157 87 741 2319
25–29 years 2027 242 117 976 3362
30–34 years 1889 227 93 868 3077
35–39 years 1221 140 77 595 2033
40–44 years 507 62 31 307 907
45+ yearsa 289 69 18 237 613
Total 7658 941 434 3942 12975
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Significant RRRs are shown in bold. For the age of father effects, contrasts that were significant after controlling for the 18 comparisons are denoted with an *.

a

For paternal age 45+, control paternal ages ranged from 45 to 80 years (mean 50.0, median 48.0), BP w/psychosis: 45–66 (mean 49.6, median 49.0); BP w/o psychosis: 45–57 (mean 49.1, median 47.5), and schizophrenia and schizoaffective: 45–78 (mean 50.1, median 48.0).

Subsequent to completion of the primary analysis and in consideration of conventions that group schizoaffective disorder-bipolar type (SA-B) with bipolar disorder, we redistributed case subjects and repeated the primary analysis. When the 747 SA-B subjects were grouped with bipolar cases with history of psychotic features, we obtained similar results (see Table III; results with interactions included are provided in Supplementary Material, Table SII). Compared to the previous analysis, in general, we observed increases in paternal age RRRs in the schizophrenia group after removing the SA-B participants (including an additional RRR that remains significant after adjusting for multiple comparisons), and decreases in the RRRs in the bipolar with psychotic features after including the SA-B participants.

TABLE III.

Relative Risk Ratios (RRR) and 95% Confidence Intervals (CI) Estimated Via Multinomial Logistic Regression for Primary Analysis With Alternative Grouping of Cases

Effect Group 1 Group 2 Bipolar w/psychosis + SA-B
Versus control		 Bipolar w/o psychosisa
Versus control		 Schizophrenia + SA-D
Versus control		 P-value
Age +20y 1.794 (1.661, 1.938) 1.539 (1.341, 1.766) 1.810 (1.697, 1.932) <0.0001
Sex Male Female 1.544 (1.387, 1.719) 0.846 (0.690, 1.033) 3.257 (2.974, 3.569) <0.0001
Race African American or Black White 1.210 (1.036, 1.409) 0.716 (0.514, 0.975) 3.038 (2.723, 3.391) <0.0001
American Indian/Alaskan Native, Asian, or Native Hawaiian/Pacific Islander White 0.530 (0.408, 0.679) 0.263 (0.134, 0.460) 0.606 (0.492, 0.741)
More Than One Race, Other, or Unknown White 1.267 (1.091, 1.467) 0.879 (0.658, 1.157) 1.058 (0.924, 1.209)
Age of father <20 years 20-24 years 0.827 (0.622, 1.088) 0.440 (0.220, 0.797) 0.912 (0.734, 1.130) <0.0001
25–29 years 20-24 years 0.998 (0.847, 1.177) 0.879 (0.660, 1.174) 0.941 (0.821, 1.078)
30–34 years 20-24 years 1.036 (0.876, 1.227) 0.795 (0.587, 1.077) 1.023 (0.889, 1.176)
35–39 years 20-24 years 0.980 (0.812, 1.182) 0.988 (0.717, 1.358) 1.070 (0.918, 1.248)
40–44 years 20-24 years 0.925 (0.719, 1.183) 0.918 (0.592, 1.389) * 1.352 (1.117, 1.634)
45+ years 20-24 years * 1.621 (1.252, 2.089) 0.933 (0.536, 1.541) * 1.488 (1.193, 1.855)
Sample size Control Bipolar w/ Psychosis + SA-B Bipolar w/o Psychosis Schizophrenia + SA-D Total
<20 years 391 76 11 186 664
20–24 years 1334 301 87 597 2319
25–29 years 2027 445 117 773 3362
30–34 years 1889 397 93 698 3077
35–39 years 1221 253 77 482 2033
40–44 years 507 104 31 265 907
45+ yearsb 289 112 18 194 613
Total 7658 1688 434 3195 12975
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Significant RRRs are shown in bold. For the age of father effects, contrasts that were significant after controlling for the 18 comparisons are denoted with an *.

a

The results for Bipolar w/p Psychosis versus Control differ slightly between Tables II and III despite the data remaining the same for this comparison. This is because multinomial logistic regression is an iterative procedure. The data in the other groups differed, and the procedure converged to estimates that were slightly different for this comparison.

b

For paternal age 45+, control paternal ages ranged from 45 to 80 years (mean 50.0, median 48.0), BP w/psychosis + SA-B: 45–66 (mean 49.2, median 48.0); BP w/o psychosis 45–57 (mean 49.1, median 47.5), and schizophrenia + SA-D: 45–78 (mean 50.4, median 48.0).

In each of the secondary analyses, paternal age was not significantly associated with family history (see Table IV). In subjects with schizophrenia or bipolar disorder, paternal age bore no statistically significant relation to a family history of schizophrenic or non-schizophrenic illness.

TABLE IV.

Odds Ratios (OR) and 95% Confidence Intervals (CI) Estimated Via Binary Logistic Regression for Secondary Analysis Predicting “No Family History“ of (i) Schizophrenia Among Bipolar Subjects; (ii) Schizophrenia Among Schizophrenic and Schizoaffective Subjects; (iii) Psychiatric Disorders Other Than Schizophrenia Among Bipolar Subjects; (iv) Psychiatric Disorders Other Than Schizophrenia Among Schizophrenic and Schizoaffective Subjects

Effect Group 1 Group 2 (1)
 (2)
 (3)
 (4)
OR (95%CI) P OR (95%CI) P OR (95%CI) P OR (95%CI) P
Age +20y 1.56 (1.41, 1.73) <0.01
Sex Male Female 1.17 (1.02, 1.35) 0.03 1.30 (1.04, 1.63) 0.02 1.65 (1.44, 1.90) <0.01
Race African American or Black White 0.38 (0.27, 0.55) <0.01 0.75 (0.64, 0.87) <0.01 1.50 (1.29, 1.74) <0.01
American Indian/Alaskan Native, Asian, or Native Hawaiian/Pacific Islander White 0.72 (0.35, 1.63) 1.31 (0.92, 1.92) 1.81 (1.30, 2.55)
More than one race, other, or unknown White 0.53 (0.38, 0.74) 0.72 (0.58, 0.88) 1.20 (0.98, 1.46)
Age of father <20 20–24 0.69 (0.36, 1.38) 0.38 0.99 (0.72, 1.37) 0.83 1.56 (0.84, 2.84) 0.81 1.14 (0.83, 1.57) 0.66
25–29 20–24 0.84 (0.56, 1.25) 1.05 (0.85, 1.28) 1.16 (0.82, 1.65) 0.98 (0.80, 1.19)
30–34 20–24 1.10 (0.72, 1.69) 1.10 (0.89, 1.36) 1.13 (0.79, 1.62) 0.87 (0.71, 1.06)
35–39 20–24 1.21 (0.75, 1.95) 0.99 (0.78, 1.25) 1.22 (0.82, 1.80) 0.94 (0.75, 1.17)
40–44 20–24 0.83 (0.47, 1.51) 1.22 (0.91, 1.64) 0.97 (0.57, 1.62) 0.95 (0.72, 1.25)
45+ 20–24 0.72 (0.41, 1.29) 1.00 (0.73, 1.37) 1.07 (0.63, 1.80) 1.02 (0.75, 1.38)
Sample size <20 years 55 218 55 218
20–24 years 244 741 244 741
25–29 years 359 976 359 976
30–34 years 320 868 320 868
35–39 years 217 595 217 595
40–44 years 93 307 93 307
45+ yearsa 87 237 87 237
Total 1375 3942 1375 3942
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Significant ORs are shown in bold.

a

For paternal age 45+, for bipolar subjects (1 and 3) ages ranged from 45 to 66 years (mean 49.5, median 49.0), and schizophrenia and schizoaffective (2 and 4): 45–78 (mean 50.1, median 48.0).

The effect sizes that we observed for schizophrenia were in line with those found in other studies which were well-summarized by Torrey and co-workers [Torrey et al., 2009]. They graphically reported odds ratios in 45+ year old fathers (compared to reference age groups) that ranged from 1.33 to 2.19 in the eight (out of nine) positive studies reported therein.

DISCUSSION

Our most remarkable finding was the marked disparity in paternal age effect in bipolar subjects with and without a history of psychotic symptoms. While the psychosis-prone subjects indeed demonstrated a significant paternal age effect, there was no association with paternal age in the non-psychosis prone bipolar subjects. The survival of this finding across two analyses, first in which cases with schizoaffective disorder-bipolar type were grouped with schizophrenia, and then with bipolar with psychotic features, strengthens this conclusion. Although the presence of a paternal age effect in all bipolar-schizophrenia spectrum case subjects was one of our a priori hypotheses, its absence in non-psychotic bipolar subjects was wholly unanticipated. Moreover, it provides a possible explanation for the heterogeneous findings in previously cited studies of paternal age effects on bipolar disorder, none of which stratified their samples according to psychosis history [Laursen et al., 2007; Frans et al., 2008; Buizer-Voskamp et al., 2011; Brown et al., 2013; Chudal et al., 2014; D’Onofrio et al., 2014]. It may well be that variations in the proportion of these subgroups contributed to the mixed findings.

The lack of a “J-shaped” relationship between paternal age and disease risk is notable. Other studies have demonstrated that very young fathers (<20 years old) have a small but significantly increased risk of fathering ill offspring than fathers in their later 20s [Miller et al., 2011]. The absence of this relationship in psychotic subjects may represent insufficient sample size in that lowest paternal age group, but we should note that other investigators have similarly failed to describe a J-shaped risk relationship. Interestingly, the only group with a significant paternal age effect in the under-20 paternal age group was those subjects diagnosed with bipolar disorder without psychosis, but the direction of the effect was to lower the risk, even suggesting a protective effect. While the sample sizes again demand caution in reaching conclusions, this finding could represent further evidence for dissociation between bipolar disorder with and without psychosis.

Another notable finding was the absence of any statistical association between family history and paternal age. As noted earlier in this report, the most commonly posited mechanism for the paternal age effect is de novo genetic mutations associated with paternal aging. Based upon this, we hypothesized that we would observe an inverse relationship between paternal age and rates of family history, which would be indicated by an OR >1 in our analysis since the outcome was “no family history.” The lack of a significant relationship between paternal age and familial disease patterns suggests that the underlying mechanisms of the paternal age effect may involve a complex interaction of heritable and non-heritable factors. While this does not rule out increased de novo mutations, it certainly points to a more complicated biological relationship between advanced paternal age and psychosis risk.

If psychosis itself is the core phenotypic expression of the paternal age effect in schizophrenia-bipolar spectrum disorders, then certain specific testable hypotheses begin to emerge. If, for instance, “all roads” to psychosis ultimately involve dopaminergic dysfunction [Seeman, 2011], then genetic and epigenetic mechanisms associated with dopaminergic neurotransmission, biosynthesis, and biometabolism may well deserve focused attention. This would, in fact, accord with Rosenfield and co-workers’ observation that paternal age-related schizophrenia subjects had a more dramatic reduction in symptom ratings when challenged with dopamine antagonists [Rosenfield et al., 2010]. Similarly, Opler and co-workers performed a post hoc analysis of parental age effects on treatment outcome in a 6-week, double-blind, placebo-controlled trial of palliperidone extended-release in 200 adolescent subjects with DSM-IV schizophrenia [Opler et al., 2013]. While paternal age did not significantly correlate to age of onset, symptom severity at study entry, or number of prior hospitalizations, it did predict superior treatment response. It would be intriguing to determine if patients with better response (rapidity and magnitude) to neuroleptics in previously published trials (such as Garver and co-worker’s “good prognosis” group [Garver et al., 2000]) had older fathers.

Next steps could include efforts to explore the genome for molecular mediators of this risk factor, and also greater delineation of the related phenotype. As is apparent to any clinician, “psychosis” is not a monolithic clinical state, but represents an array of numerous perceptual and cognitive errors. Adding further emphasis to that point, a recent consideration of hallucinations within the Research Domain Criteria (RDoC) matrix suggests a complex interplay on many levels of cognition, social process, and negative valence systems [Cuthbert and Insel, 2013; Ford et al., 2014]. Whether some but not all of these factors are associated with paternal age is strictly conjectural, and the problems of delusional thinking and conceptual disorganization pose equally complex interactions. Whether future efforts along these lines would merge with efforts to identify genetically distinct disorders, each with specific clinical phenomenology [Arnedo et al., 2014], remains to be seen.

Endophenotypic markers associated with dopaminergic function are an intriguing area for study. Analysis of existing PET data using high-affinity dopamine receptor ligands, such as with 18F-fallypride [Lehrer et al., 2010] or 11C-FLB-457 [Talvik et al., 2003] may indicate variations in binding anomalies or ligand distribution (cortical, thalamic, striatal) as a function of paternal age, possibly identifying pathophysiologic or neurodevelopmental aspects characteristic of illness related to paternal age. Analysis of large existing prepulse inhibition datasets [Swerdlow et al., 2014] with respect to paternal age could also clarify phenotypic features associated with this risk factor. Such post hoc analyses could lead to more specific, prospectively testable hypotheses and either support or refute a specific dopaminergic link to advanced paternal age. Evidence for such a link could even be incorporated into interventional algorithms for seemingly prodromal, at-risk individuals, for example, earlier initiation of dopamine antagonists in high paternal age patients.

There are limitations to our findings and conclusions. Parental age was self-reported by subjects with varying levels of cognitive function, and these data were generally not verified using other information sources. The same may be said for much of the clinical and family history information which supported diagnostic assignment, phenotypic characterization, and recordings of family history. Field study staff used their discretion regarding decisions to consult secondary information sources (family, records, treating clinicians) depending on the seeming completeness and quality of patient responses during the structured interview. However, this drawback did not impede our replication of the paternal age effect, and this fact itself is an external validation of the GPC methods and data. Further, we have no reason to believe that recall would have biased the reporting of family history of psychosis or bipolar disorder.

Available information regarding subjects’ fathers was limited to father’s date of birth. We had no information about the subject’s place in the birth order or father’s age at first paternity. So while we were able to calculate paternal age relative to the subject, we had no way to investigate the delayed fatherhood hypothesis.

Another limitation concerned the basis upon which we concluded that advanced paternal age was not associated with reduced family psychiatric history. Information regarding family psychiatric history may have been particularly vulnerable to the potential inaccuracies of self-report. The DI-PAD contains two questions regarding family history: one a query about family history of schizophrenia and the other asking about family history of disorders “other than schizophrenia.” Despite efforts to train and standardize raters’ application of the family history item (to include second degree relatives and all psychiatric conditions), the ability of subjects to give accurate information may have been limited by lack of actual knowledge of family history as well as their own, often idiosyncratic interpretations of mental disorders. Limitations concerning the accuracy of subjects’ replies to the latter question are a particular concern given its comprehensive breadth. Moreover, because subjects were not queried specifically in the DI-PAD about bipolar disorder, per se, such familial cases could have been lost in the broader, less specific pool of other familial psychiatric problems. It is conceivable that this could have introduced a Type II error, particularly if putative heritable factors that may interact with advanced paternal age are biased towards risk for the schizophrenic rather than bipolar phenotype. Given limitations in our present understanding, this is entirely speculative. The self-reported family histories may also be sensitive to bias towards reporting ill relatives as bipolar rather than the more stigmatizing schizophrenia (cultural bias), but there is no obvious reason why this would apply differentially to subjects with older versus younger fathers.

Also, despite the size of the overall GPC cohort from which the data were obtained (>33,000 cases and controls), the lack of parental age data in many subjects resulted in sample sizes that were less robust than we might have hoped. For instance, the non-psychosis prone bipolar subject group numbered only 434 subjects. As combined samples of increasing size are made available, exploration of parental age associations with other features of the schizophrenia-bipolar spectrum phenotype (negative symptoms, rapid cycling, endophenotypic traits such as neurocognitive abnormalities, prefrontal or hippocampal loss, etc.) can also be undertaken.

The proposal that psychosis is the central phenotype of the paternal age effect (vis schizophrenia-bipolar spectrum disorders) promotes a scientific agenda that follows the shift to a dimensional (such as RDoC) rather than categorical approach to psychiatric nosology. The paternal age effect in schizophrenia-bipolar spectrum disorders offers the possibility of characterizing a risk factor (later-life fathering) and its resultant neuropsychiatric consequence from genotypic to phenotypic levels.

Supplementary Material

Table S1

Additional supporting information may be found in the online version of this article at the publisher’s website.

ACKNOWLEDGEMENTS

This work was supported in part by the National Institutes of Health grants R01 MH085542 and R01 MH085548. The authors report no conflicts of interest related to this work. The Genomic Psychiatry Cohort Consortium (GPCC) investigators are: ColonyAbbott, RN, MPH, Department of Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, CA, USA; Maria Helena Azevedo, MD, PhD, Department of Psychiatry, University of Coimbra, Coimbra, Portugal; Evelyn J. Bromet, PhD, Department of Psychiatry and Behavioral Science, State University of New York, Stony Brook, NY, USA; Michael A. Escamilla, MD, Department of Psychiatry, Texas Tech University Health Sciences Center, El Paso, TX, USA; Ayman H. Fanous, MD, Department of Psychiatry, Veterans Administration Medical Center, Washington, DC, USA; Laura J. Fochtmann, MD, Department of Psychiatry and Behavioral Science, State University of New York, Stony Brook, NY, USA; Becky Kinkead, PhD, Department of Psychiatry and Behavioral Science, Emory University, Atlanta, GA, USA; James A. Knowles, MD, PhD, Department of Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, CA, USA; Fabio Macciardi, MD, PhD, Department of Psychiatry, University of California, Irvine, CA, USA; Antonio Macedo, MD, Department of Psychiatry, University of Coimbra, Coimbra, Portugal; Stephen R. Marder, MD, Department of Psychiatry, University of California, Los Angeles, CA, USA; Steven A. McCarroll, PhD, Department of Genetics, Harvard Medical School, Boston, MA, USA and Broad Institute of MIT and Harvard, Cambridge, MA, USA; Helena Medeiros, MSW, LICSW, Department of Psychiatry and the Behavioral Sciences, University of Southern California, Los Angeles, CA, USA; Christopher P. Morley, PhD, Departments of Family Medicine, Public Health & Preventive Medicine, and Psychiatry & Behavioral Sciences, State University of New York, Upstate Medical Center, Syracuse, NY; Humberto Nicolini, MD, Carracci Medical Group, Mexico City, MX; Diana O. Perkins, MD, Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA; Jeffrey J Rakofsky, MD, Department of Psychiatry and Behavioral Science, Emory University, Atlanta, GA, USA; Mark H. Rapaport, MD, Department of Psychiatry and Behavioral Science, Emory University, Atlanta, GA, USA; Pamela Sklar, MD, PhD, Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY, USA; Jordan W. Smoller, MD, ScD, Department of Psychiatry, Harvard University, Boston, MA, USA; Marquis Vawter, PhD, Department of Psychiatry, University of California, Irvine, CA, USA.

The Genomic Psychiatry Cohort Consortium authors are listed in the Acknowledgements section.

Grant sponsor:

National Institutes of Health; Grant numbers: R01 MH085542, R01 MH085548.

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Table S1
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