Interplay between Socioeconomic Markers and Polygenic Predisposition on Timing of Dementia Diagnosis

The effect of heavy smoking on retirement risk: A mendelian randomisation analysis

BACKGROUND AND AIMS

The extent to which heavy smoking and retirement risk are causally related remains to be determined. To overcome the endogeneity of heavy smoking behaviour, we employed a novel approach by exploiting the genetic predisposition to heavy smoking, as measured with a polygenic risk score (PGS), in a Mendelian Randomisation approach.

METHODS

8164 participants (mean age 68.86 years) from the English Longitudinal Study of Ageing had complete data on smoking behaviour, employment and a heavy smoking PGS. Heavy smoking was indexed as smoking at least 20 cigarettes a day. A time-to-event Mendelian Randomization (MR) analysis, using a complementary log-log (cloglog) link function, was employed to model the retirement risk.

RESULTS

Our results show that being a heavy smoker significantly increases the risk of retirement (β = 1.324, standard error = 0.622, p < 0.05). Results were robust to a battery of checks and a placebo analysis considering the never-smokers.

CONCLUSIONS

Overall, our findings support a causal pathway from heavy smoking to earlier retirement.

The Role of the Neural Exposome as a Novel Strategy to Identify and Mitigate Health Inequities in Alzheimer's Disease and Related Dementias

With the continuous increase of the elderly population, there is an urgency to understand and develop relevant treatments for Alzheimer's disease and related dementias (ADRD). In tandem with this, the prevalence of health inequities continues to rise as disadvantaged communities fail to be included in mainstream research. The neural exposome poses as a relevant mechanistic approach and tool for investigating ADRD onset, progression, and pathology as it accounts for several different factors: exogenous, endogenous, and behavioral. Consequently, through the neural exposome, health inequities can be addressed in ADRD research. In this paper, we address how the neural exposome relates to ADRD by contributing to the discourse through defining how the neural exposome can be developed as a tool in accordance with machine learning. Through this, machine learning can allow for developing a greater insight into the application of transferring and making sense of experimental mouse models exposed to health inequities and potentially relate it to humans. The overall goal moving beyond this paper is to define a multitude of potential factors that can increase the risk of ADRD onset and integrate them to create an interdisciplinary approach to the study of ADRD and subsequently translate the findings to clinical research.

Unraveling the role of plasma proteins in dementia: insights from two cohort studies in the UK, with causal evidence from Mendelian randomization

Population-based proteomics offer a groundbreaking avenue to predict dementia onset. This study employed a proteome-wide, data-driven approach to investigate protein-dementia associations in 229 incident all-cause dementia (ACD) among 3,249 participants from the English Longitudinal Study of Ageing (ELSA) over a median 9.8-year follow-up, then validated in 1,506 incident ACD among 52,745 individuals from the UK Biobank (UKB) over median 13.7 years. NEFL and RPS6KB1 were robustly associated with incident ACD; MMP12 was associated with vascular dementia in ELSA. Additional markers EDA2R and KIM1 (HAVCR1) were identified from sensitivity analyses. Combining NEFL and RPS6KB1 with other factors yielded high predictive accuracy (area under the curve (AUC)=0.871) for incident ACD. Replication in the UKB confirmed associations between identified proteins with various dementia subtypes. Results from reverse Mendelian Randomization also supported the role of several proteins as early dementia biomarkers. These findings underscore proteomics' potential in identifying novel risk screening targets for dementia.

Dental decision-making for persons with dementia: A systematic narrative review

Dental decision-making represents the establishment of a common understanding between the dental professional and the recipient of the intervention, which determines oral healthcare and dental treatment policies. Dental decision-making for persons with dementia can be challenging, and there have been no systematic reviews on this topic. Therefore, this systematic narrative review aimed to identify the current state of dental decision-making in persons with dementia. Literature search was performed using PubMed, Web of Science, Cochrane Library, CINAHL, and Google Scholar databases. Through the process of research selection, 7 articles with a high risk of bias were included in this study. This review clarified that there is limited information on the dental decision-making processes for persons with dementia. In conclusion, although this may be difficult due to different medical and socioeconomic conditions, the dilemma between the need to establish evidence for dental decision-making and medical ethics that prioritize a patient-centered position should be discussed globally in the future.

Natural language processing to identify social determinants of health in Alzheimer's disease and related dementia from electronic health records

OBJECTIVE

To develop a natural language processing (NLP) algorithm that identifies social determinants of health (SDoH), including housing, transportation, food, and medication insecurities, social isolation, abuse, neglect, or exploitation, and financial difficulties for patients with Alzheimer's disease and related dementias (ADRD) from unstructured electronic health records (EHRs).

DATA SOURCES AND STUDY SETTING

We leveraged 1000 medical notes randomly selected from 7401 emergency department and inpatient social worker notes generated between 2015 and 2019 for 231 unique patients diagnosed with ADRD at Michigan Medicine.

STUDY DESIGN

We developed a rule-based NLP algorithm for the identification of seven domains of SDoH noted above. We also compared the rule-based algorithm with deep learning and regularized logistic regression approaches. These models were compared using accuracy, sensitivity, specificity, F1 score, and the area under the receiver operating characteristic curve (AUC). All notes were split into 700 notes for training NLP algorithms, and 300 notes for validation.

DATA COLLECTION/EXTRACTION METHODS

Social worker notes used in this study were extracted from the Michigan Medicine EHR database.

PRINCIPAL FINDINGS

Of the 700 notes for training, F1 and AUC for the rule-based algorithm were at least 0.94 and 0.95, respectively, for all SDoH categories. Of the 300 notes for validation, F1 and AUC were at least 0.80 and 0.97, respectively, for all SDoH except housing and medication insecurities. The deep learning and regularized logistic regression algorithms had unsatisfactory performance.

CONCLUSIONS

The rule-based algorithm can accurately extract SDoH information in all seven domains of SDoH except housing and medication insecurities. Findings from the algorithm can be used by clinicians and social workers to proactively address social needs of patients with ADRD and other vulnerable patient populations.

Polygenic Propensity for Longevity, APOE-ε4 Status, Dementia Diagnosis, and Risk for Cause-Specific Mortality: A Large Population-Based Longitudinal Study of Older Adults

To deepen the understanding of genetic mechanisms influencing mortality risk, we investigated the impact of genetic predisposition to longevity and APOE-ε4, on all-cause mortality and specific causes of mortality. We further investigated the mediating effects of dementia on these relationships. Using data on 7 131 adults aged ≥50 years (mean = 64.7 years, standard deviation [SD] = 9.5) from the English Longitudinal Study of Aging, genetic predisposition to longevity was calculated using the polygenic score approach (PGSlongevity). APOE-ε4 status was defined according to the absence or presence of ε4 alleles. The causes of death were ascertained from the National Health Service central register, which was classified into cardiovascular diseases, cancers, respiratory illness, and all other causes of mortality. Of the entire sample, 1 234 (17.3%) died during an average 10-year follow-up. One-SD increase in PGSlongevity was associated with a reduced risk for all-cause mortality (hazard ratio [HR] = 0.93, 95% confidence interval [CI]: 0.88-0.98, p = .010) and mortalities due to other causes (HR = 0.81, 95% CI: 0.71-0.93, p = .002) in the following 10 years. In gender-stratified analyses, APOE-ε4 status was associated with a reduced risk for all-cause mortality and mortalities related to cancers in women. Mediation analyses estimated that the percent excess risk of APOE-ε4 on other causes of mortality risk explained by the dementia diagnosis was 24%, which increased to 34% when the sample was restricted to adults who were aged ≤75 years old. To reduce the mortality rate in adults who are aged ≥50 years old, it is essential to prevent dementia onset in the general population.

Ideal vitamin D and handgrip strength counteracts the risk effect of APOE genotype on dementia: a population-based longitudinal study

BACKGROUND

Higher vitamin D concentrations and grip strength contribute to lower individual-level risk of dementia, while apolipoprotein 4 (APOE e4) genotype carries increases dementia risk, but whether combination of ideal vitamin D and grip strength counteracts the risk effect of dementia related to APOE e4 genotype remains unclear. We aimed to investigate the interactions between vitamin D/grip strength and APOE e4 genotype and their association with dementia.

METHODS

The UK Biobank cohort comprised 165,688 dementia-free participants (aged at least 60 years) for the dementia analysis. Dementia was ascertained using hospital inpatient, mortality, and self-reported data until 2021. Vitamin D and grip strength were collected at baseline and divided into tertiles. APOE genotype was coded as APOE e4 non-carries and APOE e4 carries. Data were analyzed using Cox proportional hazard models and restricted cubic regression splines, with adjusted for known confounders.

RESULTS

Over the follow-up (median: 12.0 years), 3917 participants developed dementia. In women and men, respectively, compared with to the lowest tertile of vitamin D, the HRs (95% CIs) of dementia were lower in the middle [0.86 (0.76-0.97)/0.80 (0.72-0.90)] and the highest tertile [0.81 (0.72-0.90)/0.73 (0.66-0.81)]. Tertiles of grip strength showed similar patterns. In women and men, respectively, participants who had both highest tertile of vitamin D and grip strength was associated with a lower risk of dementia compared to those with both lowest tertile of these two exposures among APOE e4 genotype carries (HR = 0.56, 95% CI 0.42-0.76, and HR = 0.48, 95% CI 0.36-0.64) and APOE e4 genotype non-carries (HR = 0.56, 95% CI 0.38-0.81, and HR = 0.34, 95% CI 0.24-0.47). There were significant additive interactions between lower vitamin D/grip strength and APOE e4 genotype on dementia among women and men.

CONCLUSIONS

Higher vitamin D and grip strength were associated with a lower risk of dementia, and seemed to halve the adverse effects of APOE e4 genotype on dementia. Our findings suggested that vitamin D and grip strength may be imperative for estimating the risks of dementia, especially among APOE e4 genotype carries.

Association of laxatives use with incident dementia and modifying effect of genetic susceptibility: a population-based cohort study with propensity score matching

BACKGROUND

Constipation was associated with incidence of dementia and cognitive decline. Laxatives are the mainstay of constipation management and are commonly used among older populations for both treatment and prevention of constipation. However, the association between use of laxatives and incident dementia, and whether laxatives use may modify the effect of genetic predisposition on dementia remains unclear.

METHODS

We applied 1:3 propensity score matching to balance the baseline characteristics of the laxative users versus non-users and to reduce potential confounders using multi-variates adjusted Cox hazards regression models. We categorized genetic risk into three groups (low, middle, and high) through a genetic risk score of common genetic variants. Information on laxatives use was assessed at baseline and categories into four varieties, including bulk forming laxatives, softeners and emollients, osmotic laxatives, and stimulant laxatives.

RESULTS

Of 486,994 participants, there were 14,422 laxatives users in UK Biobank. After propensity score matching, participants with use of laxatives (n = 14,422) and matched non-laxative (n = 43,266) exposed individuals were enrolled. Over follow-up to 15 years, there were 1377 participants developed dementia (539 for Alzheimer's disease, and 343 for vascular dementia). The use of laxatives had greater risk of dementia (HR, 1.72; 95% CI:1.54-1.92), Alzheimer's disease (HR, 1.36; 95% CI: 1.13-1.63), and vascular dementia (HR, 1.53; 95% CI: 1.23-1.92). Compared to non-laxative exposed participants, those with use of softeners and emollients drugs, stimulant laxatives, and osmotic laxatives were associated with 96% (HR, 1.96; 95 CI: 1.23-3.12; P = 0.005), 80% (HR, 1.80; 95% CI: 1.37-2.37; P < 0.001), and 107% (HR, 2.07; 95% CI: 1.47-2.92; P < 0.001) higher risk of developed incident dementia, respectively. In joint effect analysis, compared to participants with low/middle genetic susceptibility and non-laxatives use, the HR (95% CIs) of dementia was 4.10 (3.49-4.81) for those with high genetic susceptibility plus use of laxatives. There was an additive interaction between laxatives use and genetic susceptibility on dementia (RERI: 0.736, 95% CI: 0.127 to 1.246; AP: 0.180, 95% CI: 0.047 to 0.312).

CONCLUSIONS

Use of laxatives was associated with higher risk of dementia and modify the effect of genetic susceptibility on dementia. Our findings suggested that attention should be paid to the relationship between laxatives use and dementia, especially in people at high genetic susceptibility.

Socioeconomic Deprivation, Genetic Risk, and Incident Dementia

INTRODUCTION

Socioeconomic factors and genetic predisposition are established risk factors for dementia. It remains unclear whether associations of socioeconomic deprivation with dementia incidence are modified by genetic risk.

METHODS

Participants in the UK Biobank aged ≥60 years and of European ancestry without dementia at baseline (2006-2010) were eligible for the analysis, with the main exposures area-level deprivation based on the Townsend Deprivation Index and individual-level socioeconomic deprivation based on car and home ownership, housing type and income, and polygenic risk of dementia. Dementia was ascertained in hospital and death records. Analysis was conducted in 2021.

RESULTS

In this cohort study, 196,368 participants (mean [SD] age=64.1 [2.9] years, 52.7% female) were followed up for 1,545,316 person-years (median [IQR] follow-up=8.0 [7.4-8.6] years). In high genetic risk and high area-level deprivation, 1.71% (95% CI=1.44, 2.01) developed dementia compared with 0.56% (95% CI=0.48, 0.65) in low genetic risk and low-to-moderate area-level deprivation (hazard ratio=2.31; 95% CI=1.84, 2.91). In high genetic risk and high individual-level deprivation, 1.78% (95% CI=1.50, 2.09) developed dementia compared with 0.31% (95% CI=0.20, 0.45) in low genetic risk and low individual-level deprivation (hazard ratio=4.06; 95% CI=2.63, 6.26). There was no significant interaction between genetic risk and area-level (p=0.77) or individual-level (p=0.07) deprivation. An imaging substudy including 11,083 participants found a greater burden of white matter hyperintensities associated with higher socioeconomic deprivation.

CONCLUSIONS

Individual-level and area-level socioeconomic deprivation were associated with increased dementia risk. Dementia prevention interventions may be particularly effective if targeted to households and areas with fewer socioeconomic resources, regardless of genetic vulnerability.

Genetic propensity, socioeconomic status, and trajectories of depression over a course of 14 years in older adults

Depression is one of the leading causes of disability worldwide and is a major contributor to the global burden of disease among older adults. The study aimed to investigate the interplay between socio-economic markers (education and financial resources) and polygenic predisposition influencing individual differences in depressive symptoms and their change over time in older adults, which is of central relevance for preventative strategies. The sample encompassing n = 6202 adults aged ≥50 years old with a follow-up period of 14 years was utilised from the English Longitudinal Study of Ageing. Polygenic scores for depressive symptoms were calculated using summary statistics for (1) single-trait depressive symptoms (PGS-DS_single), and (2) multi-trait including depressive symptoms, subjective well-being, neuroticism, loneliness, and self-rated health (PGS-DS_multi-trait). The depressive symptoms over the past week were measured using the eight-item Centre for Epidemiologic Studies Depression Scale. One standard deviation increase in each PGS was associated with a higher baseline score in depressive symptoms. Each additional year of completed schooling was associated with lower baseline depression symptoms (β = -0.06, 95%CI = -0.07 to -0.05, p < 0.001); intermediate and lower wealth were associated with a higher baseline score in depressive symptoms. Although there was a weak interaction effect between PGS-DSs and socio-economic status in association with the baseline depressive symptoms, there were no significant relationships of PGS-DSs, socio-economic factors, and rate of change in the depressive symptoms during the 14-year follow-up period. Common genetic variants for depressive symptoms are associated with a greater number of depressive symptoms onset but not with their rate of change in the following 14 years. Lower socio-economic status is an important factor influencing individual levels of depressive symptoms, independently from polygenic predisposition to depressive symptoms.

Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Interplay between polygenic propensity for ageing-related traits and the consumption of fruits and vegetables on future dementia diagnosis

BACKGROUND

Understanding how polygenic scores for ageing-related traits interact with diet in determining a future dementia including Alzheimer's diagnosis (AD) would increase our understanding of mechanisms underlying dementia onset.

METHODS

Using 6784 population representative adults aged ≥50 years from the English Longitudinal Study of Ageing, we employed accelerated failure time survival model to investigate interactions between polygenic scores for AD (AD-PGS), schizophrenia (SZ-PGS) and general cognition (GC-PGS) and the baseline daily fruit and vegetable intake in association with dementia diagnosis during a 10-year follow-up. The baseline sample was obtained from waves 3-4 (2006-2009); follow-up data came from wave 5 (2010-2011) to wave 8 (2016-2017).

RESULTS

Consuming < 5 portions of fruit and vegetables a day was associated with 33-37% greater risk for dementia in the following 10 years depending on an individual polygenic propensity. One standard deviation (1-SD) increase in AD-PGS was associated with 24% higher risk of dementia and 47% higher risk for AD diagnosis. 1-SD increase in SZ-PGS was associated with an increased risk of AD diagnosis by 66%(95%CI = 1.05-2.64) in participants who consumed < 5 portions of fruit or vegetables. There was a significant additive interaction between GC-PGS and < 5 portions of the baseline daily intake of fruit and vegetables in association with AD diagnosis during the 10-year follow-up (RERI = 0.70, 95%CI = 0.09-4.82; AP = 0.36, 95%CI = 0.17-0.66).

CONCLUSION

A diet rich in fruit and vegetables is an important factor influencing the subsequent risk of dementia in the 10 years follow-up, especially in the context of polygenetic predisposition to AD, schizophrenia, and general cognition.

Self-rated health and incident dementia over two decades: Replication across two cohorts

This prospective study examined the association between self-rated health and incident dementia in two large cohorts of middle-aged and older adults. Participants were drawn from the Health and Retirement Study (HRS, N = 13,839, Mean Age = 64.32, SD = 9.04) and the English Longitudinal Study of Ageing (ELSA, N = 4649, Mean Age = 64.44, SD = 9.97). Self-rated health and covariates were assessed at baseline in 1998 and 2002, and cognitive status was tracked for up to 21 years in HRS and 17 years in ELSA, respectively. Controlling for demographic factors, poorer self-rated health was associated with higher risk of incident dementia in HRS (HR: 1.18, 95%CI: 1.12-1.24, p < .001) and ELSA (HR: 1.38, 95%CI: 1.23-1.55, p < .001). These associations remained significant when diabetes, hypertension, smoking, physical inactivity, depressive symptoms, personality, and polygenic risk for Alzheimer's Disease were included as additional covariates or when cases occurring within the first ten years of follow-up were excluded from the analyses. There was no replicable evidence that age, sex, education, race or ethnicity moderated the association. Self-rated health is a long-term, replicable predictor of incident dementia that is independent of genetic, clinical, and behavioral risk factors.

The Influence of Socioeconomic Deprivation on Dementia Mortality, Age at Death, and Quality of Diagnosis: A Nationwide Death Records Study in England and Wales 2001-2017

BACKGROUND

Socioeconomic deprivation may be an important determinant of dementia risk, mortality, and access to diagnostic services. Premature mortality from other causes and under-representation of deprived individuals in research may lead to this effect being overlooked.

OBJECTIVE

We assessed the relationship between deprivation and dementia mortality using comprehensive death certificate data for England and Wales from 2001 to 2017.

METHODS

We used standardized mortality ratios (SMR) and a Poisson model to compare likelihood of dying from dementia in each deprivation decile. We also examined the associations of deprivation with age at death from dementia, and with likelihood of receiving a diagnosis of unspecified dementia.

RESULTS

Risk of dying from dementia was higher in more deprived deciles (Mean SMR [95% CI] in decile 1 : 0.528 [0.506 to 0.550], decile 10:0.369 [0.338 to 0.400]). In 2017, 14,837 excess dementia deaths were attributable to deprivation (21.5% of all dementia deaths that year). There were dose-response associations of deprivation with likelihood of being older at death with dementia (odds ratio [95% CI] for decile 10 (least deprived): 1.31 [1.28 to 1.33] relative to decile 1), and with likelihood of receiving a diagnosis of unspecified dementia (odds ratio [95% CI] for decile 10:0.78 [0.76 to 0.80] relative to decile 1).

CONCLUSION

Socioeconomic deprivation in England and Wales is associated with increased dementia mortality, younger age at death with dementia, and poorer access to specialist diagnosis. Reducing social inequality may have a role in the prevention of dementia mortality.

Interaction between genetic predisposition, smoking, and dementia risk: a population-based cohort study

We evaluated whether the association between cigarette smoking and dementia risk is modified by genetic predisposition including apolipoprotein E (APOE) genotype and polygenic risk (excluding the APOE region). We included 193,198 UK Biobank participants aged 60–73 years without dementia at baseline. Of non-APOE-ε4 carriers, 0.89% (95% CI 0.73–1.08%) current smokers developed dementia compared with 0.49% (95% CI 0.44–0.55%) of never smokers (adjusted HR 1.78; 95% CI 1.39–2.29). In contrast, of one APOE-ε4 allele carriers, 1.69% (95% CI 1.31–2.12%) current smokers developed dementia compared with 1.40% (95% CI 1.25–1.55%) of never smokers (adjusted HR 1.06; 95% CI 0.77–1.45); of two APOE-ε4 alleles carriers, 4.90% (95% CI 2.92–7.61%) current smokers developed dementia compared with 3.87% (95% CI 3.11–4.74%) of never smokers (adjusted HR 0.94; 95% CI 0.49–1.79). Of participants with high polygenic risk, 1.77% (95% CI 1.35–2.27%) current smokers developed dementia compared with 1.05% (95% CI 0.91–1.21%) of never smokers (adjusted HR 1.63; 95% CI 1.16–2.28). A significant interaction was found between APOE genotype and smoking status (P = 0.002) while no significant interaction was identified between polygenic risk and smoking status (P = 0.25). APOE genotype but not polygenic risk modified the effect of smoking on dementia risk.

Effect of Social Determinants of Health on Cognition and Risk of Alzheimer Disease and Related Dementias

Social determinants of health are the conditions in which people are born, work, live, and age and the wider set of forces and systems that shape the conditions of daily life. They affect every area of life, particularly health and health care. There is increasing focus on modifiable factors that affect cognition and risk of Alzheimer disease and related dementias (ADRDs). This article examines the impact of various social determinants of health, which are potentially reversible, on the incidence, prevalence, and risk of ADRDs and cognition. Various social determinants of health affect cognition and risk of ADRDs. Lower socioeconomic status (SES) and less education are associated with a higher incidence of ADRDs, whereas higher SES and education level appear to be protective, leading to a deceleration of time to diagnosis. In terms of employment, manual labor is associated with a higher risk of ADRDs. Higher body mass index in midlife and a decreasing body mass index in old age are associated with a higher risk of ADRDs. Furthermore, lower food security in early and late life is associated with a higher risk of ADRD diagnosis. Neighborhoods that are economically disadvantaged with fewer physical resources are associated with a higher risk of ADRDs. Higher levels of social engagement have a protective effect on diagnosis of ADRDs. Higher levels of stress are associated with a higher likelihood of developing ADRDs. Early-life adversity is associated with an increased risk of ADRDs, and further work in this area will be illuminating. Racial discrimination also leads to higher risk of ADRDs through the direct effect of discrimination and indirectly through lower SES, educational level, employment, and residential segregation. With an aim of reducing of ADRDs, future work in enhancing education, improving socioeconomic conditions, work, and neighborhood environments, and eliminating racial discrimination could potentially have a drastic impact.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

Predicting onset of early- and late-treatment resistance in first-episode schizophrenia patients using advanced shrinkage statistical methods in a small sample

Evidence suggests there are two treatment-resistant schizophrenia subtypes (i.e. early treatment resistant (E-TR) and late-treatment resistant (L-TR)). We aimed to develop prediction models for estimating individual risk for these outcomes by employing advanced statistical shrinkage methods. 239 first-episode schizophrenia (FES) patients were followed-up for approximately 5 years after first presentation to psychiatric services; of these, n=56 (25.2%) were defined as E-TR and n=24 (12.6%) were defined as L-TR. Using known risk factors for poor schizophrenia outcomes, we developed prediction models for E-TR and L-TR using LASSO and RIDGE logistic regression models. Models' internal validation was performed employing Harrell's optimism-correction with repeated cross-validation; their predictive accuracy was assessed through discrimination and calibration. Both LASSO and RIDGE models had high discrimination, good calibration. While LASSO had moderate sensitivity for estimating an individual risk for E-TR and L-TR, sensitivity estimated for RIDGE model for these outcomes was extremely low, which was due to having a very large estimated optimism. Although it was possible to discriminate with sufficient accuracy who would meet criteria for E-TR and L-TR during the 5-year follow-up after first contact with mental health services for schizophrenia, further work is necessary to improve sensitivity for these models.