WHAT THE STUDY ACTUALLY SAYS

Finnish data links chronotype genes to schooling and pay, in men only

Across 20,121 adults and 25 years of registry data, morningness markers predicted lower educational attainment but also lower odds of the bottom income quintile. Effects were absent in women.

Whether a person is a morning or an evening type is partly heritable. A 2019 genome-wide association study across 697,828 UK Biobank and 23andMe participants raised the number of loci associated with morningness from 24 to 351, and showed those loci track measured sleep timing: the 5% of people carrying the most morningness alleles slept, on average, 25 minutes earlier than the 5% carrying the fewest [s2].

A study published in Sleep Medicine on September 17 asks what those genetic markers predict about a person's economic position, using 25 years of Finnish registry, survey, and genetic data [s1]. The answers are inconsistent in a way the authors do not paper over.

What was analysed

The study drew on 20,121 working-aged adults representative of Finnish regions, combining genetic data with registry and survey data spanning 1992 to 2017 [s1]. Polygenic indices for morningness-eveningness were used both as direct predictors and as instruments for phenotypic chronotype, within regression and extended regression models [s1].

The outcomes were educational attainment and the likelihood of falling into the lowest income quintile [s1].

The findings pull in opposite directions

Genetic markers for morningness were monotonically negatively associated with educational attainment (p = 0.002), particularly in males [s1]. Read plainly: the more morningness alleles, the less education — which is to say evening types went further in school.

The same markers were also monotonically negatively associated with the likelihood of being in the lowest income quintile in males (p = 0.012) [s1]. So morningness alleles predicted less education but also less chance of being at the bottom of the income distribution.

The authors describe this as differential valuation of chronotype traits in education versus the labour market [s1]. The pattern emerged in the post-2000 portion of the data [s1].

The sharpest result is in a subgroup: among males with higher education, genetic predisposition to eveningness was linked to a higher likelihood of falling into the lowest income quintile (p < 0.001) [s1]. Evening types who invested in education appear, in this dataset, to have realised less income from it.

No significant associations between chronotype-related genetic markers and income were observed in females at any education level [s1].

How much weight this can carry

The authors themselves describe the effects as modest [s1]. That is the correct frame. Polygenic indices for a behavioural trait explain a small fraction of variance in that trait, and the trait in turn explains a small fraction of variance in something as multiply determined as income.

The study reports p-values rather than effect sizes in its abstract summary, which makes the practical magnitude hard to judge from the summary alone. Statistical significance across a sample of 20,121 with registry-linked outcomes can accompany a very small difference.

The sex difference is the result most likely to be an artefact of the analysis rather than a fact about the world. A null in women alongside a signal in men can arise from differences in the income distribution, in labour force participation across the period, or in statistical power, not only from a genuine sex-specific mechanism. The study does not establish which.

Nor does using genetic variants as instruments make this a causal study of chronotype's effect on income in the usual Mendelian randomisation sense. Chronotype loci are correlated with other traits, and the 2019 GWAS explicitly reports that morningness is causally associated with better mental health while showing no effect on BMI or type 2 diabetes risk [s2] — an illustration that these variants have consequences beyond sleep timing that could route to income by other paths.

Finland is one country with one education system, one labour market, and one set of daylight conditions. Extrapolation elsewhere is not warranted.

Why the question is asked at all

The framing behind this line of work is that societies run on schedules, and that schedules suit some chronotypes better than others. School start times, standard office hours, and shift structures all impose a timing that evening types must accommodate. If accommodating it carries a measurable cost, that is an argument for flexibility, and the authors make exactly that argument — workplace inclusion recognising chronotype diversity, public sleep health initiatives, and flexible work structures [s1].

The evidence here is too thin to support a policy on its own. It is thick enough to keep the question open.

What to watch

Replication in other national registry-linked genetic cohorts, particularly outside the Nordic countries; effect sizes reported in interpretable units rather than significance tests; and whether the male-only pattern survives in samples where women's labour force participation and earnings distributions differ.

This article describes an observational genetic-epidemiology study and is informational only. It is not medical advice, and polygenic indices of the kind used here are research instruments, not clinical tests.

Sources

  • [s1] Hazak A, Kantojärvi K, Liuhanen J, Sulkava S, Jääskeläinen T, Salomaa V, Koskinen S, Perola M, Paunio T, Genetic predisposition for morningness-eveningness and economic disadvantage: Evidence from Finland over 25 years, Sleep Medicine, 2025;136:106811, published online 2025-09-17.
  • [s2] Jones SE, Lane JM, Wood AR, et al., Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms, Nature Communications, 2019;10:343, published 2019-01-29.

Sources

  1. Genetic predisposition for morningness-eveningness and economic disadvantage: Evidence from Finland over 25 yearsSleep Medicine, 2025;136:106811 , September 17, 2025
  2. Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythmsNature Communications, 2019;10:343 , January 29, 2019
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