These patients had normal childhood function (PSF and PAF) similar to controls but showed deterioration during early adolescence. The SCZ_PRS in this cluster was higher than controls, but the lowest among patients and PRSs for IQ, BD, and MD were not different from controls. In line with a recent study with non-schizophrenic older adults,⁶⁹ this finding contradicts the hypothesis of an intrinsic cognitive deterioration due to a higher schizophrenia genetic predisposition. Dickinson et al.¹¹ revealed higher SCZ_PRS and lower IQ_PRS in patients with “adolescent declining” from premorbid to current IQ. However, they excluded patients with a history of substance abuse. We observed that deteriorating patients were likelier to have smoked high-potency cannabis daily, both known risk factors for psychosis.²⁴ This pattern could be responsible for the lower age of onset of this group,^64,65 as compared with the high-cognitive-functioning and the intermediate group, and could have contributed to deteriorating PAF and, hypothetically, current IQ as described in our previous study.²² However, their CUD_PRS was not different from controls and was lower than the low- the high-cognitive-functioning patients. This finding is in line with previous analyses suggesting that the probability of smoking high-potency cannabis, which increases tolerance and the frequency of cannabis use, is more dependent on the market availability than on any polygenic predispositions.^23,24 Also, nearly half of patients in this cluster ascribed to a minority ethnic group, which may have represented an additional risk factor reflecting sociocultural disadvantage.^70–72

Nevertheless, the current study cannot provide definitive causal evidence of the relationship between heavy cannabis use and a deteriorating pattern in premorbid adjustment. Cannabis was the only environmental risk factor explored because of its relationship to cognition and premorbid adjustment.²² Additionally, environmental risk factors often correlate with other environmental and polygenic risk factors,⁷³ like cannabis abuse and minority ethnic groups, urbanization, and social isolation.^74,75 Thus, one of the most recent approaches using environmental risk score algorithm⁷⁶ would help explore the hypothesis of higher environmental exposure in this cluster of FEP.

Nonetheless, we have to acknowledge some limitations of the study. First, there were marginal variations in the PRS profile between-patient groups. Although the GWASs used different power and predictive values,⁷⁷ we cannot directly compare the discriminative ability between different PRSs. Higher power would be necessary to find differences between groups with high-superimposable genetic characteristics.⁷⁸ PRSs should be further considered as dynamic sources of weighting effects of risk allele effects, as they vary each time more powered GWASs are released. In the interim, we may consider the lack of additional explanatory power of the MD_PRS⁴⁰ is due to its lower predictive value, which is less than half that SZ_PRS.³⁸

Additionally, differences could emerge in more sophisticated analyses based on subsets of genes or addressing the role of other components of the human genomic variation (eg, copy number variations), which could be present more in a cluster than in another.⁷⁹ The restriction of ancestry to solely white Europeans excluded a group of subjects, particularly at risk for psychosis, and limited the generalizability of our findings.⁷⁰ Furthermore, it is a cross-sectional study, and the reconstruction of the premorbid development is subject to self-report. However, this is not especially critical when using the PAS.⁸⁰ Equally, it would be interesting to look at the cognitive trajectories of our clusters at follow-up. The clusters resulting from a multicultural sample could only be partially replicated in different subsamples. However, the variability resulting from multi-site samples yields light on differences that studies using different methodologies in more homogeneous samples should not be able to catch. Finally, we only looked at cannabis use as an environmental risk factor and did not have the opportunity to control for socioeconomic status. Nonetheless, in future directions of this study, we could examine the distribution of other environmental risk factors between clusters.

This is, to our knowledge, the first study clustering patients with FEP by premorbid and cognitive-functioning, which suggests four discrete subgroups across the psychosis spectrum. First, cognitive impairment and premorbid deterioration were not reflected in a higher polygenic risk for schizophrenia. Indeed, the group of low-cognitive-functioning at FEP seemed to reflect neurodevelopmental impairment but no childhood social impairment. In contrast, the high-cognitive-functioning group showed childhood social impairment. Second, an intermediate cognitive group showed poor but improving childhood social and academic functioning. In contrast, a deteriorating group showed a marked deterioration in social and academic function in early adolescence, from normal functioning in childhood, probably related to an environmental impact, such as daily use of high-potency cannabis.

This study argues against the view that a pronounced and generalized deterioration in premorbid adjustment is typical of most patients who develop psychosis, especially in those more strongly predisposed to schizophrenia. Our findings could also inform care and prevention strategies⁸¹ focusing on patients’ resources and on preventable risk factors, such as cannabis misuse.