Comprehensive understanding of polyenvironmental risk factors for the development of psychosis is important. Based on a review of related evidence, we developed the Korea Polyenvironmental Risk Score (K-PERS) for psychosis. We investigated whether the K-PERS can differentiate patients with schizophrenia spectrum disorders (SSDs) from healthy controls (HCs).
We reviewed existing tools for measuring polyenvironmental risk factors for psychosis, including the Maudsley Environmental Risk Score (ERS), polyenviromic risk score (PERS), and Psychosis Polyrisk Score (PPS). Using odds ratios and relative risks for Western studies and the “population proportion” (PP) of risk factors for Korean data, we developed the K-PERS, and compared the scores thereon between patients with SSDs and HCs. In addition, correlation was performed between the K-PERS and Positive and Negative Syndrome Scale (PANSS).
We first constructed the “K-PERS-I,” comprising five factors based on the PPS, and then the “K-PERS-II” comprising six factors based on the ERS. The instruments accurately predicted participants’ status (case vs. control). In addition, the K-PERS-I and -II scores exhibited significant negative correlations with the negative symptom factor score of the PANSS.
The K-PERS is the first comprehensive tool developed based on PP data obtained from Korean studies that measures polyenvironmental risk factors for psychosis. Using pilot data, the K-PERS predicted patient status (SSD vs. HC). Further research is warranted to examine the relationship of K-PERS scores with clinical outcomes of psychosis and schizophrenia.
Schizophrenia (SZ), one of the most detrimental and common psychiatric disorders, has an annual incidence of approximately 0.015% [
Given the small proportion of the variance explained by individual single nucleotide polymorphisms (SNPs), the polygenic risk score (PRS), a weighted sum of the number of risk alleles in individuals, is now considered as a valid alternative approach and has been widely applied in research studies. A similar approach has been employed to predict conversion to psychosis by aggregating environmental risk factors. Intervention prior to the full manifestation of a disorder may delay or even prevent the onset of psychosis; early identification of those at high risk of psychosis is thus of great importance. Three tools using the aggregate score for multiple environmental risk factors have been developed: the polyenviromic risk score (PERS) [
Potentially relevant studies were identified by a comprehensive search of the PubMed, Embase, and PsychINFO electronic databases. Terms related to environmental risk in general, or to each putative risk factor (i.e., paternal age OR parental socioeconomic status [SES] OR pregnancy complication OR obstetric complications OR urbanicity OR child adversity/trauma/abuse OR cannabis/substance use OR recent life events) were combined with psychosis OR psychotic disorders OR SZ. The searches were limited to studies related to the ERS, PERS, and PPS, which measure multiple environmental risk factors, and to systematic reviews or meta-analyses of studies of putative risk factors. To determine the “population proportion” (PP) of risk factors in Korea, annual or survey reports issued by government-affiliated agencies (Ministry of Health and Welfare, Statistics Korea, Korea Land and Housing Corporation) were searched.
The ERS and PPS scores were estimated by scaling the odds ratios (ORs) or relative risks (RRs) with PP for each risk factor, whereas the PERS score was obtained by simply summing the ORs of the risk factors. We assumed that the former two tools may provide more valid estimates of the risk factors. Thus, we decided to consider the appropriateness only of the risk factors included in those two tools. Members of the Korea Early Psychosis Study (KEPS) team reviewed the risk factors included in the two tools. We decided that it would not yet be appropriate to include two factors, cannabis use and immigrant/ethnic minority status, in a tool designed for Koreans, although both factors are becoming increasingly important social issues in Korea. Also, premorbid IQ, olfactory identification ability, and pollution were considered to be impractical for clinical use. Paternal age, parental SES, and adult life events were not included in the original PPS [
Pilot K-PERS data were obtained from patients with SSDs, including SZ, schizoaffective disorder, schizophreniform disorder, and psychotic disorder not otherwise specified (n=130 and 217 for the K-PERS-I and -II, respectively), participating in the KEPS [
For the K-PERS, low parental SES was defined as receiving medical aid at the time of the respondent’s birth. Urbanicity was considered present when a person was raised in a city for more than 50% of their early life (from birth to 12 years old). Adult life events referred to at least two adverse events including living alone, financial hardship, and difficulties in social relationships and occupational or academic functioning, experienced at the age of ≥19 years at least 6 months prior to the development of psychotic symptoms. The PP values for paternal age, parental SES, urbanicity, childhood trauma, and clinical high risk for psychosis were acquired from official Korean data. However, as we did not find an appropriate data source for adult adverse life events, the same PP values used for the PPS [
To accurately determine parental SES, a 7-point scale has been devised, on which low SES is reflected by on the presence of six factors (father’s/mother’s income in the lowest quintile, father/mother unemployed or outside the labor market, and father’s/mother’s highest educational level less than high school) [
For the K-PERS-I, we only calculated the scores for the first five factors listed in
Among modern psychiatry disciplines, biological psychiatry has been the dominant research field, especially genetic and brain imaging studies. Most researchers in the field of molecular genetics now believe that many genes are involved (the polygenic theory) in the development of SZ, so have abandoned the single-gene approach [
Numerous large-scale population-based studies have reported associations between various environmental factors and the prevalence of psychosis and psychotic symptoms [
In the case of the PRS, many studies have explored its predictive value with respect to conversion in persons at clinical high risk [
Several limitations of this study should be mentioned. First, we decided to use OR and RR data from Western studies on relationships between polyenvironmental risk factors and SZ, so the K-PERS may not truly reflect Koreans’ experiences. To address this shortcoming, large-scale epidemiologic studies investigating relationships between environmental risk factors and psychosis should be performed. Second, ethnicity and immigration were not incorporated into the K-PERS. Due to increasing immigration from other Asian countries, this should be considered in future versions of the K-PERS. Third, conflict and stress related to family members was not considered in the K-PERS; however, this factor was also not included in the ERS, PERS, and PPS due to a lack of evidence. Nevertheless, several studies have suggested an important role of the family environment in the development of psychosis [
The online-only Data Supplement is available with this article at
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Sung-Wan Kim and Euitae Kim, a contributing editor of the
Conceptualization: Young-Chul Chung. Data curation: Yan-Hong Piao, Bong-Ju Lee, Sung-Wan Kim, Jung-Jin Kim. Formal analysis: Je-Chun Yu, Kyu-Young Lee, Seung-Hwan Lee. Funding acquisition: Young-Chul Chung, Seung-Hee Won. Investigation: Seung-Hyun Kim, Eui-Tae Kim. Methodology: Bong-Ju Lee, Clara Tammy Kim. Project administration: Young-Chul Chung. Resources: Shi-Hyun Kang. Software: Fatima Zahra Rami. Supervision: Young-Chul Chung. Validation: Paolo Fusar-Poli. Visualization: Dominic Oliver. Writing—original draft: Young-Chul Chung, Eun Jin Jeon. Writing—review & editing: Young-Chul Chung, Eun Jin Jeon.
This study was supported by grants from the Korean Mental Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea (HL19C0015), and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (HI18C2383).
Risk factors and its score for the K-PERS-I
Risk factor | Cut-off |
OR | log10 (OR) | Population proportion (%) |
Prevalence |
Population average |
PPS |
K-PERS-I |
||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Foreign | Korea | Foreign | Korea | Foreign | Korea | Foreign | Korea | Exposed | Nonexposed | Exposed | Nonexposed | |||
Paternal age at birth | >35 | >35 | 1.28 [ |
0.107 | 80.00 [ |
44.22 [ |
0.8 | 0.442 | 0.086 | 0.047 | 0 | -1 | 0.5 | -0.5 |
Parental SES | Low | Receiving medical aid | 1.3 [ |
0.114 | 8.4 [ |
3.02 [ |
0.084 | 0.030 | 0.010 | 0.003 | 1 | 0 | 1 | 0 |
Urbanicity | Population density >50,000 | Living in city | 2.19 [ |
0.340 | 73.60 [ |
92.87 [ |
0.736 | 0.929 | 0.250 | 0.316 | 1 | -2.5 | 0 | -3 |
Childhood trauma | ≥Moderate in the CTQ | ≥Moderate level of any trauma | 2.87 [ |
0.458 | 11.76 [ |
0.42 [ |
0.118 | 0.005 | 0.054 | 0.002 | 4 | -0.5 | 4.5 | 0 |
Adult life events | ≥Moderate life events | ≥Moderate level of at least two adverse events | 5.34 [ |
0.728 | 25 [ |
25 [ |
0.25 | 0.25 | 0.182 | 0.182 | 5.5 | -2 | 5.5 | -2 |
Clinical high risk state for psychosis | ≥2 in the APSS | ≥29 in the K-ESI [ |
9.32 [ |
0.969 | 13.94 [ |
1.26 [ |
0.139 | 0.013 | 0.1352 | 0.012 | 8.5 | -1.5 | 10 | 0 |
Premorbid IQ | <93.6 | 0.47 [ |
-0.323 | 33.48 [ |
0.335 | -0.110 | 2 | -1 | ||||||
Olfactory identification ability | Impaired ability | 0.19 [ |
-0.7213 | 24.00 [ |
0.24 | -0.173 | 5.5 | -1.5 | ||||||
Non-right handedness | Non-right handedness | 1.58 [ |
0.199 | 5.90 [ |
0.059 | 0.012 | 2 | 0 | ||||||
Immigration | 1st or 2nd generation immigrant | 2.1 [ |
0.322 | 16.80 [ |
0.168 | 0.054 | • Not immigrant: -0.5 | |||||||
• 1st generation immigrant: from North Africa, 3 and from other regions, 2 | ||||||||||||||
1.68 [ |
0.225 | 9.20 [ |
0.092 | 0.021 | • 2nd generation immigrant: from North Africa, 2.5 and from other regions, 1.5 | |||||||||
Ethnicity | Ethnicity | 2.83–4.87 [ |
• White: -2 | |||||||||||
• Black Caribbean: in low ethnic density area, 6; in medium ethnic density area, 5.5; in high ethnic density area, 3.5 | ||||||||||||||
• Others: in low ethnic density area, 3,5; in medium ethnic density area, 3; in high ethnic density area, 1 |
incidence rate ratio.
APSS, Adolescent Psychotic-Like Symptom Screener; CTQ, Childhood Trauma Questionnaire; K-ESI, Korea-Eppendorf Schizophrenia Inventory; PPS, Psychosis Polyrisk Score; Kostat, Statistics Korea; NHISC, National Health Insurance Service Corporation; LH, Korea Land & Housing Corporation
Risk factors and its score for the K-PERS-II
Risk factor | Cut-off |
RR from meta-analysis | log(RRj) | Population proportion (%) |
ERS | K-PERS-II | ||||
---|---|---|---|---|---|---|---|---|---|---|
Foreign | Korea | Foreign | Korea | Foreign | Korea | |||||
Paternal age at birth | <40 | <25 | 1.06 | 0.025 | 92.1 | 1.688 | 1.02 | 1.09 | 0 | 0 |
25–29 | 1 | 0 | 10.300 | 1.09 | -0.5 | |||||
30–34 | 1.06 | 0.025 | 42.763 | 1.09 | 0 | |||||
35–39 | 1.13 | 0.053 | 32.160 | 1.09 | 0 | |||||
40–50 | 40–44 | 1.22 | 0.086 | 7.1 | 9.900 | 1.02 | 1.09 | 0.5 | 0.5 | |
45–49 | 1.21 | 0.083 | 1.791 | 1.09 | 0.5 | |||||
>50 | ≥50 | 1.66 [ |
0.220 | 0.8 [ |
0.370 [ |
1.02 | 0.039 | 2 | 2 | |
Obstetric complications | Birth weight <2.5 kg | 1.67 | 0.223 | 3.6 | 5.744 | 0.008 | 0.012 | 2 | 2 | |
Birth weight ≥2.5 kg | 1 [ |
0 | 96.4 [ |
94.260 [ |
0.008 | 0.012 | 0 | 0 | ||
Parental SES (exposed/non exposed) | Father’s income in the lowest quintile | 2.22/1 | 0.346/0 | 21.016/78.984 | 21.016/78.984 [ |
1.26/1.26 | 1.26/1.26 | 2.5/-1 | 2.5/-1 | |
Mother’s income in the lowest quintile | 1.74/1 | 0.241/0 | 22.836/77.165 | 13.8/86.2 [ |
1.17/1.17 | 1.10/1.10 | 1.5/-0.5 | 2/-0.5 | ||
Father being unemployed or otherwise outside the labor market | 2.53/1 | 0.403/0 | 14.933/85.067 | 14.933/85.067 [ |
1.23/1.23 | 1.23/1.23 | 3/-1 | 3/-1 | ||
Mother being unemployed or otherwise outside the labor market | 1.58/1 | 0.199/0 | 25.517/74.484 | 43.5/56.5 [ |
1.15/1.15 | 1.25/1.25 | 1.5/-0.5 | 1/-1 | ||
Father’s highest educational level less than high school | 1.47/1 | 0.167/0 | 28.368/71.6328 | 1.309/98.691 [ |
1.13/1.13 | 1.01/1.01 | 1/-0.5 | 1.5/0 | ||
Mother’s highest educational level less than high school | 1.79/1 [ |
0.253/0 | 47.847/52.153 [ |
1.675/98.325 [ |
1.38/1.38 | 1.01/1.01 | 1/-1.5 | 2.5/0 | ||
Urbanicity | Population density by three equal tertiles | County | 1.156 | 0.063 | 33.3 | 7.135 | 1.59 | 1.75 | -1.5 | -2 |
City | 1.546 | 0.189 | 33.3 | 48.404 | 1.59 | 1.75 | 0 | -0.5 | ||
Metropolitan city | 2.067 | 0.315 | 33.3 | 44.461 [ |
1.59 | 1.75 | 1.5 | 0.5 | ||
Childhood adversity | Exposed/Non exposed (≥moderate level of any trauma) | 2.78/1 [ |
0.444/0 | 27/73 | 1.48/1.48 | 2.5/-15 | ||||
Neglect | 2.9/1 | 0.462/0 | 0.033/99.967 | 0.001/0.001 | 4.5/0 | |||||
Emotional abuse | 3.4/1 | 0.531/0 | 0.056/99.944 | 0.001/0.001 | 5.5/0 | |||||
Physical abuse | 2.95/1 | 0.470/0 | 0.039/99.961 | 0.001/0.001 | 4.5/0 | |||||
Sexual abuse (≥moderate level of each trauma) | 2.38/1 [ |
0.377/0 | 0.008/99.991 [ |
0.001/0.001 | 4/0 | |||||
Recent life events | Exposed/non exposed (≥moderate life events) | Exposed/non exposed (≥moderate level of at least two adverse events) | 3.19/1 [ |
0.504/0 | 25/75 [ |
25/75 [ |
1.55/1.55 | 1.55/1.55 | 3/-2 | 3/-2 |
Cannabis use | No exposure | 1 | 0 | 70 | 0.089 | -1 | ||||
Little to moderate exposure | 1.405 | 0.148 | 15 | 0.089 | 0.5 | |||||
High exposure | 2.775 [ |
0.443 | 15 [ |
0.089 | 3.5 | |||||
Ethnic minority status | Native | 1 | 0 | 92.4 | 0.053 | 0.5 | ||||
Any origin | 2.3 | 0.362 | 7.6 | 0.053 | 3 | |||||
Black | 4 | 0.602 | 1.3 | 0.053 | 6 | |||||
White | 1.8 | 0.255 | 2.8 | 0.053 | 2 | |||||
Other | 2 [ |
0.301 | 3.5 [ |
0.053 | 2.5 |
SES, socioeconomic status
Comparison of K-PERS-I between patients and healthy controls
Patients (N=217) | Healthy controls (N=154) | p-value | |
---|---|---|---|
Paternal age at birth | -0.24 (0.44) | -0.37 (0.34) | 0.0011 |
Parental SES | 0.40 (0.49) | 0.17 (0.37) | 2.6E-07 |
Urbanicity | -0.80 (1.33) | -0.27 (0.86) | 4.9E-06 |
Childhood trauma | 2.90 (2.16) | 0.88 (1.79) | <0.05 |
Adult life events | 1.77 (3.76) | -1.37 (2.09) | <0.05 |
Total | 4.04 (4.99) | -0.96 (3.15) | <0.05 |
Values are presented as mean (SD, standard deviation). K-PERS, Korea Polyenvironmental Risk Score; SES, socioeconomic status
Correlation of the K-PERS-I with DI and PANSS
DI | PANSS |
||||
---|---|---|---|---|---|
Total | Positive symptoms | Negative symptoms | General psychopathology | ||
Paternal age at birth | -0.02 (0.79) | -0.06 (0.36) | -0.06 (0.36) | -0.05 (0.48) | -0.05 (0.43) |
Parental SES | 0.09 (0.21) | 0.01 (0.94) | 0.00 (0.97) | -0.02 (0.82) | 0.02 (0.76) |
Urbanicity | -0.09 (0.19) | -0.02 (0.73) | -0.04 (0.53) | 0.00 (0.96) | -0.02 (0.73) |
Childhood trauma | 0.05 (0.46) | -0.03 (0.67) | 0.08 (0.22) | -0.11 (0.12) | -0.04 (0.58) |
Adult life events | 0.08 (0.22) | -0.11 (0.09) | -0.05 (0.5) | -0.14 (0.05) | -0.11 (0.12) |
Total | 0.07 (0.32) | -0.11 (0.11) | -0.02 (0.82) | -0.15 (0.03) | -0.11 (0.12) |
Values are presented as correlation coefficient (p-value). K-PERS, Korea Polyenvironmental Risk Score; DI, duration of illness; PANSS, Positive and Negative Syndrome Scale; SES, socioeconomic status
Comparison of K-PERS-II between patients and healthy controls
Patient group (N=130) | Control group (N=126) | p-value | |
---|---|---|---|
Paternal age at birth | 0.04 (0.13) | 0.02 (0.10) | 0.30 |
Obstetric complications | 0.12 (0.48) | 0.08 (0.39) | 0.43 |
Parental SES | 2.82 (3.47) | 2.94 (3.59) | 0.80 |
Urbanicity | -0.61 (0.93) | -0.85 (0.63) | 0.02 |
Childhood adversity | 5.84 (5.51) | 1.94 (3.74) | 2.1E-10 |
Emotional abuse | 2.88 (2.76) | 0.87 (2.02) | 2.0E-10 |
Neglect | 1.14 (1.97) | 0.64 (1.58) | 0.0258 |
Physical abuse | 1.45 (2.11) | 0.36 (1.22) | 7.5E-07 |
Sexual abuse | 0.37 (1.16) | 0.06 (0.50) | 0.01 |
Recent life events | 0.96 (2.47) | -0.41 (2.34) | 7.5E-06 |
Total | 9.18 (7.16) | 3.71 (6.74) | 1.4E-09 |
Values are presented as mean (SD, standard deviation). K-PERS, Korea Polyenvironmental Risk Score; SES, socioeconomic status
Correlation of the K-PERS-II with DI and PANSS
DI | PANSS |
||||
---|---|---|---|---|---|
Total | Positive symptoms | Negative symptoms | General psychopathology | ||
Father’s age at patient’s birth | -0.05 (0.56) | -0.05 (0.61) | -0.02 (0.9) | -0.1 (0.26) | -0.01 (0.88) |
Obstetrics and perinatal complication | 0.14 (0.11) | -0.00 (0.99) | 0.04 (0.67) | -0.06 (0.53) | 0.01 (0.88) |
SES | 0.08 (0.39) | -0.13 (0.13) | -0.08 (0.37) | -0.16 (0.08) | -0.11 (0.21) |
Urbanization | -0.1 (0.28) | -0.04 (0.62) | -0.12 (0.18) | 0.05 (0.58) | -0.05 (0.58) |
Childhood trauma | 0.0 (0.96) | -0.04 (0.67) | 0.01 (0.88) | -0.12 (0.17) | -0.00 (0.98) |
Emotional abuse | 0.02 (0.76) | -0.01 (0.95) | 0.08 (0.35) | -0.13 (0.13) | 0.03 (0.75) |
Neglect | 0.06 (0.53) | -0.06 (0.53) | -0.07 (0.44) | -0.07 (0.43) | -0.02 (0.81) |
Physical abuse | -0.09 (0.3) | -0.04 (0.67) | 0.01 (0.95) | -0.09 (0.33) | -0.02 (0.83) |
Sexual abuse | 0.03 (0.75) | -0.01 (0.94) | -0.03 (0.76) | 0.02 (0.85) | -0.01 (0.92) |
Difficulties of adulthood | -0.04 (0.64) | -0.1 (0.27) | -0.14 (0.13) | -0.05 (0.56) | -0.07 (0.39) |
Total score | 0.02 (0.80) | -0.13 (0.13) | -0.09 (0.32) | -0.18 (0.03) | -0.09 (0.32) |
Values are presented as correlation coefficient (p-value). K-PERS, Korea Polyenvironmental Risk Score; DI, duration of illness; PANSS, Positive and Negative Syndrome Scale; SES, socioeconomic status