|Year : 2018 | Volume
| Issue : 1 | Page : 1-7
Familial aggregation of mood disorders among relatives of schizophrenia probands admitted in a hospital in South-Eastern Nigeria: A family comparative study
Justus Uchenna Onu1, Jude Uzoma Ohaeri2
1 Department of Clinical Services, Federal Neuropsychiatric Hospital, New Haven, Enugu, Enugu State, Nigeria
2 Department of Psychological Medicine, University of Nigeria, Nsukka, Enugu State, Nigeria
|Date of Web Publication||17-Apr-2018|
Dr. Justus Uchenna Onu
Federal Neuropsychiatric Hospital, New Haven, Enugu
Source of Support: None, Conflict of Interest: None
Introduction: The debate on the current nosological status of schizophrenia and mood disorders as distinct entities is very active among scholars. There is a paucity of genetic epidemiological data to contribute an African perspective to this debate. Aim: This study aimed to assess the morbid risk of mood disorders in the relatives of schizophrenia probands, in comparison with the families of a sample of healthy controls. Subjects and Methods: This study elicited the information on the morbid risk of mood disorders among 5259 relatives of schizophrenia probands (n = 138) and 6734 relatives of healthy controls (n = 138) through direct interview of patients, available relatives of patients and the comparison group. The family history approach using the Family Interview for Genetic Studies was utilised to obtain information on the morbid risk of all relatives that could be recalled. The diagnosis of available relatives was confirmed using the Diagnostic Interview for Genetic Studies. Morbid risk estimates were calculated using the Weinberg shorter method for age correction. Results: Morbid risk for mood disorders in the first-, second- and third-degree relatives of schizophrenia probands were 1.39% (95% confidence interval [CI] = 1.23–1.55), 0.86% (95% CI = 0.80–0.92) and 0.55% (95% CI = 0.53–0.57), respectively, compared with 0.45% (95% CI = 0.39–0.51), 0.11% (95% CI = 0.07–0.51) and 0.08% (95% CI = 0.06–0.09), respectively, for the healthy comparison group. Conclusion: This result supports the impression that familial risk for mood disorders is significantly higher among relatives of schizophrenia patients, compared with healthy controls and that there could be familial relationship between the predisposition to schizophrenia and mood disorders.
Keywords: Control, mood-disorders, morbid-risk, relatives, schizophrenia-probands
|How to cite this article:|
Onu JU, Ohaeri JU. Familial aggregation of mood disorders among relatives of schizophrenia probands admitted in a hospital in South-Eastern Nigeria: A family comparative study. Niger Postgrad Med J 2018;25:1-7
|How to cite this URL:|
Onu JU, Ohaeri JU. Familial aggregation of mood disorders among relatives of schizophrenia probands admitted in a hospital in South-Eastern Nigeria: A family comparative study. Niger Postgrad Med J [serial online] 2018 [cited 2019 Sep 21];25:1-7. Available from: http://www.npmj.org/text.asp?2018/25/1/1/230195
| Introduction|| |
Schizophrenia is a heterogeneous group of disorders thought to be of polygenic origin, which develops through heterogeneous mechanisms and shows a complex pattern of inheritance. Although genetic risk factors are important in the causation of major psychiatric disorders, the exact pathophysiological mechanisms of major psychiatric disorders are largely unknown. Therefore, diagnoses are presently defined as descriptive syndromes on the basis of expert consensus, with difficulties in delineating diagnostic boundaries.,
The current psychiatric nosology accepts schizophrenia and mood disorders as distinct entities in tandem with earlier Kraepelin's fundamental distinction between dementia praecox (schizophrenia) and manic-depressive insanity.,, This divide has continued to generate debate among scholars. The proponents of dichotomy base their arguments on differences in symptom patterns and the course of illness; while the proponents of the continuum model argue that there is no clear distinction between schizophrenia and mood disorders, especially at the genetic level. The later school of thought is reminiscent of the unitary hypothesis of Wilhelm Griesinger, namely, that all forms of psychosis are surface variations of a single underlying disease process. However, clinical features such as psychosis, mood dysregulation and cognitive impairment are known to transcend both diagnostic categories. In addition, doubts still remain about the boundaries and the degree to which schizophrenia and mood disorders constitute entirely distinct entities. The aetiological relations among these disorders remain a topic of active debate even after the introduction of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. Some authors have argued that the manual did not meet the conditions for a strong interpretation of the medical model of diseases because it lacked rigorously defined biological markers to differentiate each disorder. Therefore, the National Institute of Mental Health research domain criteria project was launched to fund research towards a new nosology based on neuroscience and behavioural science rather than descriptive psychopathology as championed by Jaspers.
An enduring question in the genetics of major psychiatric disorders is the extent of overlap between schizophrenia and mood disorders. Many family and twin studies have documented familial and heritable overlap between major psychiatric disorders.,,,, Well-designed family studies have reported increased morbid risk of mood disorders among relatives of schizophrenia probands.,, Rasic et al., in a recent meta-analysis, reported 1.62 fold risks of mood disorders among offspring of parents with schizophrenia, while studies in Asian populations have reported morbid risk figures ranging from 3.0% to 4.1%.,, These data tend to suggest some familial relationship between the predisposition to schizophrenia and mood disorders. To further support the psychotic-affective continuum debate, a recent genome-wide association analysis identified four specific single-nucleotide polymorphisms with pleiotropic effects on both childhood and adult-onset psychopathologies including autism, attention deficit hyperkinetic disorder, schizophrenia, major depressive disorders and bipolar disorders. Despite the burgeoning data supporting the hypothesis that psychotic, as well as affective disorders, aggregate in families of individuals with schizophrenia, some researchers have found no familial overlap between schizophrenia and affective disorders., These scholars tend to support the distinctiveness of both disorders as currently enshrined in the psychiatric nosology. However, on the whole, family, twin and molecular genetic studies have supported the hypothesis that there is overlap in the genetic liability among these disorders. This has far-reaching consequences for clinical practice, namely, risk counselling, diagnosis and treatment prediction.
There is a paucity of genetic epidemiological data on the familial relationship between schizophrenia and mood disorders, to contribute an African perspective to this debate. This perspective is important because it has been noted that the allelic variation in African populations is thought to be richer than in other populations, which in theory might present a different clinical picture. In this regard, it is worthwhile to note that the majority of previous studies were conducted in Western and Asian populations.,, Limited data from Africa report increased morbid risk of mood disorders among relatives of schizophrenia probands compared to healthy control groups.,, These studies involved small sample sizes of patients (36–50 probands with 293 and 330 first-degree relatives, respectively) and addressed psychiatric morbidity only in the first-degree relatives. Their findings will benefit from replication, for refutation or increased robustness, using a larger sample size of patients and a wider network of relatives. The aim of this study was to determine the morbid risk of mood disorders in the first-, second- and third-degree relatives of schizophrenia probands, in comparison with the families of a sample of healthy control group, who are not hospital staff.
| Subjects and Methods|| |
Ethical approval was obtained from the Ethical Committee of the Federal Neuropsychiatric Hospital (FNH) Enugu, Nigeria with reference number FNHE/HCS and T/REA/VOL. 1/176. International ethical norms and standards were strictly adhered to; written informed consent was obtained from all the participants. Participation was voluntary.
Study design and population
This was a comparative family history study with a cross-sectional design. The study was carried out among the in patients of the FNH, Enugu, which is one of the eight specialist Psychiatric Hospitals established by the Federal Government of Nigeria. It is located within Enugu metropolis and provides mental health care for the South Eastern part of Nigeria and the neighbouring geopolitical zones. The comparative group consisted of staff of all cadres at the Enugu North Local Government Secretariat. Enugu North Local Government is one of the local councils located within Enugu metropolis.
Consecutive inpatients with the diagnosis of schizophrenia, who gave permission for their relatives to be approached, were recruited into the study. Patients aged 18–64 years whose diagnosis was made at least 1 year before sampling (to allow for stability of diagnosis) were included in the study. Patients with schizophrenia of suspected organic aetiology, medical, or psychiatric co-morbidities or both were excluded through a detailed medical history and full physical examination (including neurological examination). Only in patients were involved in this study because of the lengthy time required for interview and to locate many family members, who may be available during visit hours. Patients were interviewed when they were in a stable clinical condition (fully conscious and could optimally participate during the interview without the need for emergency chemical and/or physical restraint).
The comparison group consisted of physically and mentally healthy local government workers (not including health staff) aged above 45 years. This was to ensure that the comparison group had passed the maximal risk period and less likely to develop the disorder under investigation (the maximal risk period for schizophrenia is 15–45).
Study subjects from the various wards were recruited as listed in the hospital's admission register, which is a record of patients by date of admission and provisional diagnosis. A total of 250 patients were admitted into the various wards in the 6-month period of the study which was from 1st October 2015 to 31st March 2016. One hundred and sixty had a clinical diagnosis of schizophrenia by the unit consultant. They were approached and after complete description of the study, five declined to give consent due to unwillingness to participate. The remaining 155 were recruited for the study after obtaining a written informed consent. They were reassessed, and 138 meet the criteria for schizophrenia using ICD-10. Fifteen of the 155 subjects were excluded because of the presence of comorbid medical illnesses and/or substance use disorders. An additional two were excluded because the illness had not lasted for up to 1 year.
In computing the required sample size for the study, we used the findings of Maier et al., for the following reasons:First, they studied first-, second- and third-degree relatives and healthy control group. Second, they used similar instruments to obtain family history information. Third, our comparison group was also from the community. Based on their finding that the morbid risk of schizophrenia in first-degree relatives was 5.0%, compared with 0.8% for the control group, we computed the required sample size by using these figures to substitute in the Cochran formula for comparison groups (2z 2 pq/d 2) and arrived at 124, each, for patients and comparison group.
The healthy subjects
Workers with a major psychiatric diagnosis or history of chronic medical illnesses, such as diabetes mellitus, epilepsy, hypertension and duodenal ulcer were excluded from the study. This was done using the screening sections of the Mini International Neuropsychiatric Interview (MINI) to screen out the presence of mental disorders and thorough medical history to exclude the presence of physical conditions.
Procedure and measurement
Diagnosis of schizophrenia was made using the ICD-10 criteria for schizophrenia and confirmed using the MINI. One senior resident doctor (JUO) in psychiatry applied the MINI. He was trained to apply the study instruments by a senior psychiatrist with experience in the use of these instruments. At the preliminary stage of the study, the research team took turns in interviewing patients not involved in the study; and the study commenced when the senior research psychiatrist judged that the interviewers could confidently apply the questionnaires. Joint rating sessions were done periodically throughout the study, to ensure that the standard interview process was being adhered to.
The family interview for patients, patients' relatives and the control group was done by another set of two senior psychiatry residents (NBN and MCI), similarly trained by the senior psychiatrist, using the Family Interview for Genetic Studies (FIGS). They used the constructed family tree as a guide, to review the family pedigree of the participants and then used the FIGS to collect family information. Patients' relatives that looked after the patients in the ward or who intermittently visited the patients were, in a convenient room within the ward, interviewed directly using the Diagnostic Interview for Genetic Studies (DIGS). The information on relatives who could not be reached by the research interviewers was obtained through proxy interview (that is obtaining the history of the unavailable relatives by interviewing available relatives) using the FIGS. For the comparison group, all the family information was gathered through proxy interview.
For every first-, second- and third-degree relative with symptoms suggestive of mood disorders, the research interviewer made a detailed summary. Two consultant psychiatrists reviewed all available information (DIGS, FIGS, other relevant side information and copies of medical records) pertaining to the probands' relatives and the relatives of the control group. Best estimate lifetime psychiatric diagnosis according to the ICD-10 criteria was determined independently and then finalised by consensus. Two levels of diagnoses were possible none and definite.
The statistical analysis was done using the Statistical Package for Social Sciences, version 18 (SPSS Inc. 2009, PASW Statistics for windows, Chicago, Illinois).
Results were first calculated as frequencies. Group comparisons were done using Chi-square test (categorical variables) and Student's t-test, where appropriate (continuous variables). All tests were two-tailed and the level of significance was set at P < 0.05. The Weinberg method for age correction was used to calculate the lifetimes at risk (morbid risk) for each group of relatives. This assigns a value of 1 for every relative over the age of risk, 0.5 for those within the age of risk and 0 for those below the age of risk. The Weinberg estimator for lifetime morbid risk is given by: W-MR = A/(A + 0.5 U2 + U3). Where, A = the number of affected relatives of a certain class (e.g. first-degree, etc.). U1 = the number of unaffected subjects who were younger than the minimal risk period of age. U2 = the number of unaffected subjects who were within the period of risk. U3 = the number of unaffected subjects who were older than the maximal risk period age. W-MR = Weinberg-Morbid risk. The limit for age of risk for mood disorders were 15–59 years as used in previous Nigerian studies., The corrected denominator, often referred to by the German term Bezugsziffer, or BZ, is meant to approximate the number of lifetime at-risk subjects.
| Results|| |
A total of 276 subjects (138 schizophrenia patients, 138 healthy comparison group) and their 11,993 relatives (5259 relatives of patients of which 1315 were directly interviewed; and 6734 for the control, all interviewed by proxy) participated in the study. The result of the sociodemographic profile of the 276 participants is presented in [Table 1]. As expected from the methodology, the healthy comparison group was significantly older (49.07 ± 3.1 years) than the patient group (31.8 ± 10.4 years) (P < 0.001); they were more likely to be married (P < 0.001), better educated (P < 0.001) and by definition, were all employed (P < 0.001).
|Table 1: Sample characteristics of schizophrenia patients and healthy group|
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The sociodemographic characteristics of the first-, second- and third-degree relatives of the probands and the comparison group are shown in [Table 2]. There was no significant difference between the mean age of the first-, second- and third-degree relatives of the probands and the comparison group.
|Table 2: Sociodemographic details of the first-, second-, and third-degree relatives of patients and healthy group|
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[Table 2] also shows that the frequency distribution of kinship characteristics for both groups was similar. The number of first-degree relatives of the patients who were <15 and >50 years of age was 136 and 350, respectively; while those for the comparison group were, respectively, 160 and 374.
The morbid risk estimates for mood disorders among first-, second- and third-degree relatives of schizophrenia patients were 1.39% (95% confidence interval [CI] = 1.23–1.55), 0.86% (95% CI = 0.80–0.92) and 0.55% (95% CI = 0.53–0.57), compared to 0.45% (95% CI = 0.39–0.51), 0.11% (95% CI = 0.07–0.51) and 0.08% (95% CI = 0.06–0.09), of the first-, second- and third-degree relatives of the healthy comparison group, respectively. This is summarised in [Table 3].
|Table 3: Morbid risk estimates of mood disorders (definite cases) among first-, second- and third-degree relatives of schizophrenia probands and healthy group|
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| Discussion|| |
The study aimed at determining the familial aggregation of mood disorders among relatives of schizophrenia probands. This study is one of the few genetic epidemiological studies in Africa that examined the morbid risk of mood disorders among relatives of schizophrenia probands in comparison with healthy controls.
The sociodemographic profile of the probands shows that they were mostly young (mean age 31.76 ± 10.40), single (76.8%), unemployed (63.8%) and educated (84.8% had at least high school education). Although the mean age of schizophrenia probands in Okewole et al. study was higher than our study, our participants were similar to theirs in other characteristics such as marital status, employment status, sex, religion and level of education. The finding that most of the participants were single or not living with their spouses may reflect the tendency of patients with schizophrenia to remain single due to the difficulty in forming close social bonds and the social exclusion that characterises the disorder. It is noteworthy that there was no significant difference in sex between the probands and the comparison group [Table 1] and that the significant difference in educational status was actually accounted for by the employment requirement of the comparison group (as government workers), in which case none of them would be illiterate. Over three-quarters of both groups had at least secondary school education. However, we are of the opinion that these sociodemographic differences do not affect our morbid risk estimates because the estimates were for the relatives of the two groups, who were found to be mostly similar in sociodemographic characteristics [Table 2].
Morbid risk of mood disorders
The morbid risk of mood disorders in the first-, second- and third-degree relatives of schizophrenia probands were 1.39% (95% CI = 1.23–1.55), 0.86% (95% CI = 0.80–0.92) and 0.55% (95% CI = 0.53–0.57), respectively. These figures are at least two times higher than those of the corresponding relatives of the healthy comparison group: 0.45% (95% CI = 0.39–0.51), 0.11% (95% CI = 0.07–0.51) and 0.08% (95% CI = 0.06–0.09), respectively. As these comparison figures do not overlap, they are judged to be significantly different.
The figure for the first-degree relatives in the present study is higher than the 0.42% reported in the first-degree relatives of schizophrenia probands in a previous African study, but similar to 1.62-fold risk reported in a recent meta-analysis. However, a similar study from Taiwan reported a higher morbid risk for mood disorders (4.1% and 3.3% using Weinberg and Kaplan-Maier estimation of morbid risk, respectively) in the first-degree relatives of schizophrenia patients. Previous studies have shown conflicting results regarding heritability estimates of affective disorders among probands with schizophrenia spectrum disorders. One study found that the first-degree relatives of schizophrenia probands had lower risk of affective illness than those of a healthy control group, while other studies found a higher risk of affective illness in the first-degree relatives of schizophrenia probands compared to that of the control groups., In summary, the notion of familial overlap between schizophrenia and mood disorders is widely supported by current literature but with variability in the morbid risk estimates across studies from different continents.
There is a possible reason for the lower morbid risk of mood disorders in our study compared with the studies from the Western and Asian populations. These differences may be partly explained by the proportion of the directly interviewed relatives in the present study. The proportion of directly interviewed relatives in this study was about 25%; this is smaller than that of previous family studies in Western and Asian countries. For example, the figures for directly interviewed relatives were 85% for a study in United States, 75.6% for a study in Germany, and 57% for a study in Taiwan. This explanation looks more plausible when our study is compared with the previous report from Africa that utilised only the family history method. Okewole et al. used only family history method and reported the morbid risk of mood disorder of 0.42% in the first-degree relatives of schizophrenia probands; this is lower than our figure of 1.39%. Although family history method is known to underestimate true rates of psychiatric disorders in the relatives, the family study method, on the other hand, is prone to selection and participation biases. We find the above explanation unlikely to explain all the differences in the estimates from various continents. Despite that the majority of relatives of probands in our study were interviewed indirectly (75%), the use of multiple informants and sourcing information from medical records of relatives that had contact with our facility has the potential to increase the possibility of identifying true cases. Other possible reasons include the differences in the verbal expression of mood symptoms in African and Western populations. Despite evidence for the universality of experience of depressive symptoms among different populations, differences exist in the verbal expression of symptoms and salience attributed to clinical manifestations. Payne found that clinicians underdiagnose unipolar mood disorders when culturally expressed symptoms are present. However, the controversy over the tendency of Nigerians to express psychiatric distress with bodily symptoms such as internal heat, crawling sensations, emptiness or heaviness of the head, has now been resolved with the placement of these symptoms in the category of somatisation disorder/somatic symptom disorder in the current systems of nosology., Although it is reasonable to suspect that the stigma attached to mental illness in Africa may reduce the likelihood of relatives revealing details of sick family members for fear of possible social consequences such as social exclusion, we found no reason to doubt the sincerity of the history given by the participants.
There are some possible explanations for the higher morbid risk of mood disorders among relatives of schizophrenia probands than the comparison group. First, it may be argued that the higher morbid risk of mood disorders in schizophrenia probands is due to overdiagnosis of probands' relatives owing to surveillance bias. This is unlikely in our study because relatives' diagnoses were assigned rigorously. Second, there might be an overlap between schizophrenia and mood disorders at the genetic level. However, the genetic basis of this overlap is still subject to much controversy, with recent findings suggesting polygenic inheritance. Accumulating evidence from clinical, epidemiological and molecular genetic studies suggest that some genetic risk factors overlap between neuropsychiatric disorders. Many family and twin studies have documented familial and heritable overlap between subsets of five psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism and attention deficit hyperactivity disorder).,, Genetic association studies have provided some support for these associations at a molecular level., A recent meta-analytic study implicated a specific biological pathway (voltage-gated calcium-channel signalling) as a contributor to the pathogenesis of several psychiatric disorders. The impression of genetic overlap, supported by the findings in this study, needs to be explained within the context of the prevailing phenomenological categorical model of psychiatric classification that treats schizophrenia and mood disorders as separate disorders. While there are obviously important clinical distinctions between these disorders, the data are consistent with either a continuum from affective to psychotic illness on which diagnostic categories are imposed or with a set of distinct disease entities with overlapping symptomatology that is not distinguished effectively in the current psychiatric nosology. An important implication of this impression is that in phenotyping for genome-wide association studies, investigators might consider the psychosis spectrum as a single phenotype. This is already being considered, as consortia such as the Psychiatric Genomics Consortium have a cross-disorders group charged with the task of investigating overlaps.
Third, the burden of care on relatives of schizophrenia patients may be a confounder. The demands of caregiving are enormous and they include, making payments, supervising patients, dealing with the social stigma and exclusion associated with the disorder, along with coping with the emotional distress that the symptoms of the disorder cause. Available literature indicates that the burden on carers of people with severe mental disorders is considerably high and that their well-being and mental health may become seriously impaired.,,
One of the limitations of this study is the use of the family history method in the majority of the relatives; although it saved cost and time, but lack of sensitivity for many psychiatric disorders is a major drawback. Direct interview of all relatives, while having its problems such as selection bias, could have made more rigorous diagnosis possible, especially for the comparison group. However, in this study, the magnitude of this problem may have been attenuated by the use of multiple informants and also the fact that about 25% of the relatives were directly interviewed.
Second, although our sample size was larger than those of previous studies from our region, a larger proband and control group sample size would have been probably advantageous.
Third, the choice of the healthy controls from local government staff is undoubtedly better than hospital staff. However, a community sample would have been more representative.
| Conclusion|| |
This study adds to the body of genetic epidemiological research that provides evidence that there could be familial overlap between schizophrenia and mood disorders. Given that there is higher morbid risk of mood disorders among relatives of schizophrenia probands compared with the relatives of controls, a plausible model is that a number of genes confer risk of psychotic-affective disorder in general, while another small set of genes – or epigenetic or environmental factors – determine where on the continuum the disorder will fall if it develops. An important implication is that in phenotyping for genome-wide association studies, investigators might consider the psychosis spectrum as a single phenotype.
The authors would like to thank Dr. J. U. Onwukwe, the Medical Director, FNH, Enugu, for providing the enabling environment and some logistic support for this study. In addition, we would like to thank Mr. Lewis Okanchi of the Federal School of Statistics for his insightful comments on the statistical methods, Drs. Inechi, Nweze and Johnson for assistance in interviewing the relatives and Drs. Unaogu and Ubochi for supervisory roles. We are grateful to the patients, their relatives and staff of the local government, for freely giving of their time to participate in the study.
Financial support and sponsorship
The project was self–financed by the first author as a personal initiative.
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization. International Classification of Diseases and Related Health Problem (ICD-10). 10th
ed. Geneva: World Health Organization; 1994.
American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders. 5th
ed. Washington, DC: American Psychiatric Association; 2013.
Kraepelin E. Psychiatry: A Textbook for Students and Physicians (Translation of the Psychiatrie). 6th
ed. Canton, MA: Science History Publications; 1990.
Andreasen NC. A unitary model of schizophrenia: Bleuler's “fragmented phrene” as schizencephaly. Arch Gen Psychiatry 1999;56:781-7.
Parnas J. The RDoC program: Psychiatry without psyche? World Psychiatry 2014;13:46-7.
Gershon ES, DeLisi LE, Hamovit J, Nurnberger JI Jr., Maxwell ME, Schreiber J, et al.
A controlled family study of chronic psychoses. Schizophrenia and schizoaffective disorder. Arch Gen Psychiatry 1988;45:328-36.
Akiskal HS. The Overlap of Affective and Schizophrenic Spectra. Cambridge, England: Cambridge University Press; 2007.
Van Snellenberg JX, de Candia T. Meta-analytic evidence for familial coaggregation of schizophrenia and bipolar disorder. Arch Gen Psychiatry 2009;66:748-55.
Chang CJ, Chen WJ, Liu SK, Cheng JJ, Yang WC, Chang HJ, et al.
Morbidity risk of psychiatric disorders among the first degree relatives of schizophrenia patients in Taiwan. Schizophr Bull 2002;28:379-92.
Chou IJ, Kuo CF, Huang YS, Grainge MJ, Valdes AM, See LC, et al.
Familial aggregation and heritability of schizophrenia and co-aggregation of psychiatric illnesses in affected families. Schizophr Bull 2017;43:1070-8.
Rasic D, Hajek T, Alda M, Uher R. Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: A meta-analysis of family high-risk studies. Schizophr Bull 2014;40:28-38.
Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: A genome-wide analysis. Lancet 2013;381:1371-9.
Frangos E, Athanassesnas G, Tsitourides S, Katsanou N, Alexandrakou P. Prevalence of DSM-111 schizophrenia among the first-degree relatives of schizophrenic probands. Acta Psychiatry Scand 1985;72:382-6.
Tsuang MT, Winokur G, Crowe RR. Morbidity risks of schizophrenia and affective disorders among first-degree relatives of patients with schizophrenia, mania, depression, and surgical conditions. J Psychiatry Res 2004;38:3-15.
Campbell MC, Tishkoff SA. African genetic diversity: Implications for human demographic history, modern human origins, and complex disease mapping. Annu Rev Genomics Hum Genet 2008;9:403-33.
Kendler KS, Gruenberg AM, Tsuang MT. Psychiatric illness in first-degree relatives of schizophrenic and surgical control patients. A family study using DSM-III criteria. Arch Gen Psychiatry 1985;42:770-9.
Maier W, Hallmayer J, Minges J, Lichtermann, D. Morbid risks in relatives of affective, schizoaffective, and schizophrenic patients – Results of a family study affective and schizoaffective. In: Marneros A, Tsuang MT, editors. Disorders: Similarities and Differences. New York, NY: Springer-Verlag; 1990. p. 201-7.
Adamson TA. Psychiatric illness in first degree relatives of Nigerian schizophrenic and surgical control patients. Trop Geogr Med 1993;45:73-6.
Okewole AO, Adewuya AO, Makanjuola RO, Owoeye OA. Morbidity profile of first-degree relatives of probands with schizophrenia: A comparison with mood disorder and healthy control. Soc Psychiatry Psychiatry Epidemiol 2015;50:389-95.
Gureje O, Bamidele R, Aderibigbe YA. Heritability of schizophrenia. A controlled family history investigation in Nigeria. Br J Psychiatry 1994;164:481-6.
McGuffin P, Owen MJ, O'Donovan MC, Thapar A, Gottesman II. Seminars in Psychiatric Genetics. 1st
ed. London: Gaskell; 1994. p. 30-2.
Maier W, Lichtermann D, Franke P, Heun R, Falkai P, Rietschel M, et al.
The dichotomy of schizophrenia and affective disorders in extended pedigrees. Schizophr Res 2002;57:259-66.
Cochran WG. Sampling Techniques. 2nd
ed. New York: John Wiley & Sons Incorporated.; 1963.
Camil F, David MS, Michael P. On estimation and comparison of lifetime morbid risks. J Data Sci 2010;8:645-64.
Browne G, Courtney M. Schizophrenia housing and supportive relationships. Int J Ment Health Nurs 2007;16:73-80.
Baron M, Gruen R, Rainder JD. A family study of schizophrenia and normal control probands: Implication for the spectrum concept of schizophrenia. Am J Psychiatry 1985;142:447-55.
Maier W, Lichtermann D, Minges J, Hallmayer J, Heun R, Benkert O, et al.
Continuity and discontinuity of affective disorders and schizophrenia. Results of a controlled family study. Arch Gen Psychiatry 1993;50:871-83.
Payne JS. Influence of race and symptom expression on clinicians' depressive disorder identification in African Americans. J Soc Soc Work Res 2012;3:162-77.
Binitie A. A factor-analytical study of depression across cultures (African and European). Br J Psychiatry 1975;127:559-63.
Ebigbo PO. Development of a culture specific (Nigeria) screening scale of somatic complaints indicating psychiatric disturbance. Cult Med Psychiatry 1982;6:29-43.
Glessner JT, Hakonarson H. Common variants in polygenic schizophrenia. Genome Biol 2009;10:236.
Shaw SH, Kelly M, Smith AB, Shields G, Hopkins PJ, Loftus J, et al.
A genome-wide search for schizophrenia susceptibility genes. Am J Med Genet 1998;81:364-76.
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: A tool for genome-wide complex trait analysis. Am J Hum Genet 2011;88:76-82.
O'Donovan MC. What have we learned from the psychiatric genomics consortium? World Psychiatry 2015;14:291-3.
Cuipers P, Stam R. The challenges of mental health caregiving. Arch Psychiatry Nurs 2011;25:339-49.
Oshodi YO, Adeyemi JD, Aina OF, Suleiman TF, Erinfolami AR, Umeh C, et al.
Burden and psychological effects: Caregiver experiences in a psychiatric outpatient unit in Lagos, Nigeria. Afr J Psychiatry (Johannesbg) 2012;15:99-105.
Ohaeri JU. Caregiver burden and psychotic patients' perception of social support in a Nigerian setting. Soc Psychiatry Psychiatry Epidemiol 2001;36:86-93.
Ohaeri JU. The burden of caregiving in families with a mental illness: A review of 2002. Curr Opin Psychiatry2003;16:457-65.
[Table 1], [Table 2], [Table 3]