Your DNA may predict your future success more than your upbringing

A major twin study is shedding new light on the long running debate over nature versus nurture, suggesting that genetics may play a far larger role in future success than many people realize.

Researchers found that IQ measured at age 23 was strongly connected to socioeconomic status by age 27, including education, occupation, and income. According to the study, much of that connection appears to be tied to genetics rather than upbringing alone.

The findings come from the German TwinLife project, a long term research effort designed to examine how genes and environment shape people's lives over time.

Twin Study Explores IQ and Life Outcomes

The research followed about 880 people, including both identical and fraternal twins. Roughly half of the participants were identical twins, who share all of their genes, while the others were fraternal twins, who share about half.

Because the twins were raised in the same households, researchers could compare how much of the differences between them came from genetics versus environment.

The participants took IQ tests at age 23. Four years later, researchers evaluated their socioeconomic status by looking at factors such as education level, occupation, and income.

The results were striking. The researchers estimated that IQ was about 75 percent genetically predicted. They also found that the link between IQ and socioeconomic status was largely explained by genetics, ranging from 69 percent to 98%.

"We knew this before, but this study shows even more clearly that we are driven by our genes and become who we are largely because of them," says personality psychologist Petri Kajonius, whose study was published in Scientific Reports.

Rethinking the "Silver Spoon" Idea

The findings challenge the familiar idea that success mainly comes from growing up in a wealthy or highly educated family.

"The so-called 'silver spoon' isn't as big as you might think. Your home life also depends on your genes," Kajonius explains.

That does not mean family environment has no influence. Instead, the research suggests that inherited traits may shape how people respond to opportunities, education, and life experiences.

The study also raises difficult questions about social mobility and public policy. If genetics strongly influence life outcomes, how much can educational programs and social interventions really change a person's long term trajectory?

 "The study shows that we are born with different genetic predispositions and that it is difficult to bring about long-term change in this regard through policy measures."

What the Findings Mean for Parents and Young Adults

Kajonius says the results may actually offer some reassurance to parents.

Many parents worry that mistakes in raising their children could permanently affect their future success. But the findings suggest parents may have less control over long term socioeconomic outcomes than commonly believed.

That does not mean parenting or educational support are unimportant. Targeted interventions can still help people succeed. However, the research suggests there may be limits to how much external factors can reshape deeply rooted traits over time.

For young adults, the findings may encourage a different perspective on career choices and achievement.

Rather than focusing only on maximizing status or income, Kajonius suggests people may benefit more from pursuing the things they naturally enjoy and excel at.

Important Limitations of the Study

The researchers note several important caveats.

One limitation is that the study did not directly control for parents' IQ or socioeconomic status. Another issue is that studies like this can struggle to fully separate genetics from environment because the two often interact in complex ways.

For example, genetic traits may express themselves differently depending on a person's upbringing or life circumstances. The researchers say this interaction could partly inflate the estimated genetic influence of IQ, potentially by as much as 15 percentage points.

Even with those limitations, the study adds to growing evidence that genetics plays a powerful role in shaping intelligence, opportunity, and life outcomes.

Journal Reference:

1. Petri J. Kajonius. Longitudinal associations between cognitive ability and socioeconomic status are partially genetic in nature. Scientific Reports, 2026; 16 (1) DOI: 10.1038/s41598-026-37786-3

Courtesy:

Lund University. "Your DNA may predict your future success more than your upbringing." ScienceDaily. ScienceDaily, 6 May 2026. <www.sciencedaily.com/releases/2026/05/260505234624.htm>. 

Mysterious RNA led scientists to a hidden layer of cancer

 

The journey began with T3p, a small RNA molecule detected in breast cancer but not in normal tissue. When it was first described in 2018, it stood out as unusual. That initial finding launched a six-year effort to systematically identify similar orphan non-coding RNAs (oncRNAs) across major cancer types, determine which ones actively contribute to disease, and test whether they could help monitor patients using simple blood tests.

In our newly published study, we describe how this work progressed from analyzing large cancer genome datasets to developing machine learning models, conducting large-scale functional experiments in mice, and ultimately confirming the clinical relevance of these RNAs in nearly 200 breast cancer patients using blood samples.

Cancer-Specific OncRNAs Are Widespread

One of the first major discoveries was that this phenomenon was not limited to breast cancer. By examining small RNA sequencing data from The Cancer Genome Atlas across 32 different cancer types, we identified approximately 260,000 cancer-specific small RNAs. We refer to these molecules as oncRNAs, and they were present across every cancer type analyzed.

Their distribution was not random. Each cancer type displayed its own distinct oncRNA expression pattern. Lung cancers, for example, showed a different set of oncRNAs compared with breast cancers. Using these patterns, machine learning models were able to classify cancer types with 90.9% accuracy. When tested in a separate group of 938 tumors, classification accuracy remained high at 82.1%.

Differences also emerged within individual cancers. Basal breast tumors showed oncRNA patterns distinct from luminal tumors, suggesting additional subtypes that may not yet be fully defined. These findings indicate that oncRNAs reflect fundamental aspects of cancer cell state. Patterns of oncRNA presence and absence function as "digital molecular barcodes" that capture cancer identity at multiple levels, including tumor type, subtype, and cellular state.

Some OncRNAs Actively Drive Tumor Growth

Although oncRNAs serve as powerful biomarkers, we also wanted to understand whether some of them directly influence cancer progression. Specifically, we asked whether cancer cells could use these newly emerged RNA molecules to activate oncogenic pathways.

To test this, we created screening libraries containing about 400 oncRNAs from breast, colon, lung, and prostate tumors. These RNAs were introduced into cancer cells using lentiviral vectors. In half of the cases, we increased oncRNA expression. In the other half, we reduced expression using "Tough Decoy" constructs. The modified cells were then implanted into mice to determine which oncRNAs enhanced tumor growth.

Roughly 5% of the oncRNAs produced clear biological effects in xenograft mouse models. Two breast cancer oncRNAs were examined more closely. One triggered epithelial-mesenchymal transition, an essential step in cancer progression and metastasis. The other activated E2F target genes, promoting cell proliferation. Both significantly accelerated tumor growth and increased metastatic colonization in independent cell line models.

When we examined patient tumor data, we found that tumors expressing these same oncRNAs displayed similar pathway changes. Observing consistent biological patterns in TCGA samples and experimental models strengthened our confidence in the findings.

Cancer Cells Release OncRNAs Into the Bloodstream

Perhaps the most clinically important discovery was that cancer cells actively release many of these oncRNAs into the bloodstream. Tracking these circulating RNAs provides insight into how patients are responding to treatment.

We analyzed cell-free RNA from 25 cancer cell lines across 9 tissue types and found that about 30% of oncRNAs are actively secreted. To confirm their clinical relevance, we studied serum samples from 192 breast cancer patients enrolled in the I-SPY 2 neoadjuvant chemotherapy trial. Blood samples were collected before and after treatment, and we calculated the change in total oncRNA burden (ΔoncRNA below).

That single measurement proved highly informative. Patients with high residual oncRNA levels after chemotherapy had nearly 4-fold worse overall survival. This association remained significant even after accounting for standard clinical indicators such as pathologic complete response and residual cancer burden.

This was our most ambitious goal. Although we knew oncRNAs could be detected in blood, it was uncertain whether they would provide meaningful information in real patient samples. Detecting such a strong signal from just 1 milliliter of serum was unexpected.

A New Approach to Monitoring Minimal Residual Disease

These findings address a significant clinical challenge. Monitoring minimal residual disease in breast cancer using markers such as cell-free DNA is difficult because tumors often release very little DNA into the bloodstream, particularly in early stages. RNA-based monitoring may offer an advantage because cancer cells actively secrete RNA rather than passively shedding DNA.

What Comes Next for OncRNA Research

Important biological and clinical questions remain. How do functional oncRNAs exert their effects? Do they interact with proteins or with other RNAs? Could tracking oncRNA changes in real time guide treatment decisions? Might they help detect recurrence earlier or improve patient stratification? Answering these questions will require more extensive research and larger prospective clinical trials.

At the same time, translation is already underway. The discovery that oncRNAs generate cancer-specific signals in blood is moving toward clinical application. We are collaborating with the biotech company Exai Bio (Hani is a co-founder) to develop oncRNA-based diagnostics. The company has been building artificial intelligence models and assembling diverse datasets to improve cancer detection and classification.

Translational research depends on many contributors. When analyzing tens of thousands of samples computationally, it is easy to forget that each one represents a person who volunteered for research, donated blood, and hoped their participation would help others. Honoring those contributions through careful and rigorous science motivates our entire team.

We believe oncRNAs represent a newly recognized class of cancer-emergent molecules that function both as drivers of disease and as biomarkers. By making this resource openly available, we hope to accelerate progress and open new avenues of research in cancer biology.

 

Journal Reference:

1. Jeffrey Wang, Jung Min Suh, Brian J. Woo, Albertas Navickas, Kristle Garcia, Keyi Yin, Lisa Fish, Taylor Cavazos, Benjamin Hänisch, Daniel Markett, Gillian L. Hirst, Lamorna Brown-Swigart, Laura J. Esserman, Laura J. van ‘t Veer, Hani Goodarzi. Systematic annotation of orphan RNAs reveals blood-accessible molecular barcodes of cancer identity and cancer-emergent oncogenic drivers. Cell Reports Medicine, 2026; 102577 DOI: 10.1016/j.xcrm.2025.102577 

Courtesy:

Arc Institute. "Mysterious RNA led scientists to a hidden layer of cancer." ScienceDaily. ScienceDaily, 17 February 2026. <www.sciencedaily.com/releases/2026/02/260216084527.htm>.