When Cells Become Questions
A reflection on autism research, science, and the limits of understanding
A brief summary of the research
A recent study published in Nature investigates how different genetic forms of autism affect early brain development. Researchers took ordinary cells (such as skin or blood cells) from individuals with and without autism and reprogrammed them into stem cells. These were then grown into small, brain-like structures—so-called cortical organoids—that model early stages of human brain development.
By following these organoids over time, the researchers found something striking:
Although different genetic mutations initially produce different effects, these differences tend to converge as development progresses. In other words, many distinct biological starting points may lead into shared developmental pathways, particularly affecting how neurons form, mature, and connect.
This suggests that autism, despite its many causes, may involve common underlying biological processes—especially in early brain development.
When understanding begins with hesitation
I must admit:
When I first read this research, I hesitated.
There was something in me that resisted.
Something that felt close to what Kierkegaard once called fear and trembling.
Not because the science was weak—
on the contrary, it is among the most advanced we have.
But because of what it does:
It takes living human cells, reprograms them,
and allows them to grow into small, brain-like structures—
organoids—so that we may study development as it unfolds.
There is something both fascinating and unsettling in this.
A new kind of window
The promise is clear.
For decades, autism research has been marked by fragmentation:
many causes, many pathways, many stories.
But here, something different appears.
Even if autism begins in many different genetic variations,
these differences may converge—
meeting in shared biological pathways during early brain development.
Different beginnings.
A kind of shared unfolding.
From a scientific perspective, this is powerful.
It offers coherence where there has been complexity.
But it also raises a deeper question:
What kind of understanding is this?
Understanding as explanation—and as interpretation
Here I find myself turning, almost instinctively, to Gadamer.
For Gadamer, understanding is never just explanation.
It is always interpretation—
a meeting between what we study and who we are.
Science seeks what can be measured,
what can be repeated,
what can be placed—so to speak—“two lines under.”
And this study does exactly that—beautifully.
It maps gene expression,
tracks development over time,
identifies networks that seem to regulate other networks.
It gives us clarity.
But Gadamer would gently remind us:
Understanding is not only about what we can see—
but about how we make sense of what we see.
And here, something remains open.
The human being beyond the model
Because what is being studied is not the human being as lived.
Not the child who struggles—or flourishes.
Not the adult who experiences the world differently.
Not the quiet, often invisible work of making meaning in one’s own life.
What is studied are cells.
Signals.
Patterns.
Important, yes.
Necessary, even.
But still only one layer of what it means to be human.
Heidegger and the question of technology
At this point, Heidegger enters the room.
Not to reject science—
but to ask a different kind of question:
What happens when we begin to understand life primarily as something that can be produced, modeled, and controlled?
The stem cell, once part of a human body,
is now part of a laboratory system.
It is reprogrammed.
Directed.
Observed.
Nothing here is careless.
Everything is ethically regulated.
And yet—
Heidegger might say that something subtle shifts:
The human being begins to appear as something that can be
revealed through technical processes.
Not wrong.
But incomplete.
Kierkegaard and the single individual
And then, perhaps most importantly,
Kierkegaard.
Because in all convergence, all patterns, all shared pathways,
he would insist on one thing:
The single individual cannot be reduced.
Autism, in lived experience, is never just a pathway.
Never just a network of genes.
It is a way of being in the world.
A way of relating.
A way of sensing, understanding, and sometimes struggling.
There is no convergence that can fully capture that.
Between insight and humility
So where does that leave us?
Not in rejection.
Not in fear.
But perhaps in something more demanding:
a double movement.
On the one hand:
- To recognize the power of this research
- To acknowledge that it reveals something real about human development
On the other:
- To resist the temptation to believe that this is the whole story
Because it is not.
A quiet closing
There is something deeply human in wanting to understand.
To look closer.
To see patterns.
To find connections where there was confusion.
This research is part of that movement.
But perhaps practical philosophy asks us to remain aware of something else:
That understanding is not only something we achieve—
it is also something we live into.
And maybe the most important thing we can say is this:
Even when science brings us closer to the mechanisms of life,
the meaning of a human life still asks to be understood—
not in the laboratory, but in the encounter.
References
Gordon, A., Yoon, S.-J., Bicks, L. K., Martín, J. M., Pintacuda, G., Arteaga, S., Wamsley, B., Guo, Q., Elahi, L., Dolmetsch, R. E., Bernstein, J. A., O’Hara, R., Hallmayer, J. F., Lage, K., Pașca, S. P., & Geschwind, D. H. (2026). Developmental convergence and divergence in human stem cell models of autism. Nature, 651, 707–715. https://doi.org/10.1038/s41586-025-10047-5
Gadamer, H.-G. (2004). Truth and method (2nd rev. ed.). Continuum. (Original work published 1960)
Heidegger, M. (1977). The question concerning technology and other essays. Harper & Row.
Kierkegaard, S. (1985). Fear and trembling (A. Hannay, Trans.). Penguin Classics. (Original work published 1843)
Even when science brings us closer to the mechanisms of life,the meaning of a human life still asks to be understood—not in the laboratory, but in the encounter.
This text was written by me in conversation with OpenAI/ChatGPT